{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(\"train.csv\");\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 12 columns):\n",
      "PassengerId    891 non-null int64\n",
      "Survived       891 non-null int64\n",
      "Pclass         891 non-null int64\n",
      "Name           891 non-null object\n",
      "Sex            891 non-null object\n",
      "Age            714 non-null float64\n",
      "SibSp          891 non-null int64\n",
      "Parch          891 non-null int64\n",
      "Ticket         891 non-null object\n",
      "Fare           891 non-null float64\n",
      "Cabin          204 non-null object\n",
      "Embarked       889 non-null object\n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.6+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0253ae2ad0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAk0AAADuCAYAAAAk7TMxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJhEREZEcVJpEREREclBpEhEREcnh/wEa9B4RaImCsAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0253b067d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#### Check if the gender plays a role in survival\n",
    "fig = plt.figure(figsize=(10,4))\n",
    "fig.add_subplot(121)\n",
    "df.Survived[df['Sex'] == 'male'].value_counts().plot(kind='pie')\n",
    "fig.add_subplot(122)\n",
    "df.Survived[df['Sex'] == 'female'].value_counts().plot(kind='pie')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Mr', 'Mrs', 'Miss', 'Master', 'Don', 'Rev', 'Dr', 'Mme', 'Ms',\n",
       "       'Major', 'Lady', 'Sir', 'Mlle', 'Col', 'Capt', 'the Countess',\n",
       "       'Jonkheer'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#### Split the titles from the passenger names which is itself a feature but also help in calculating missing median age values\n",
    "df['Name'] = df['Name'].map(lambda x: x.split(',')[1].split('.')[0].strip())\n",
    "titles = df['Name'].unique()\n",
    "titles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Miss</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mrs</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Mr</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  Name     Sex   Age  SibSp  Parch  \\\n",
       "0            1         0       3    Mr    male  22.0      1      0   \n",
       "1            2         1       1   Mrs  female  38.0      1      0   \n",
       "2            3         1       3  Miss  female  26.0      0      0   \n",
       "3            4         1       1   Mrs  female  35.0      1      0   \n",
       "4            5         0       3    Mr    male  35.0      0      0   \n",
       "\n",
       "             Ticket     Fare Cabin Embarked  \n",
       "0         A/5 21171   7.2500   NaN        S  \n",
       "1          PC 17599  71.2833   C85        C  \n",
       "2  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3            113803  53.1000  C123        S  \n",
       "4            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age'].fillna(-1, inplace=True)\n",
    "\n",
    "medians = dict()\n",
    "for title in titles:\n",
    "    median = df.Age[(df[\"Age\"] != -1) & (df['Name'] == title)].median()\n",
    "    medians[title] = median\n",
    "for index, row in df.iterrows():\n",
    "    if row['Age'] == -1:\n",
    "        df.loc[index, 'Age'] = medians[row['Name']]\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2QAAAFoCAYAAAA4tTiaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHZAppZRSSimlVCA6IFNKKaWUUkqpQP4fYPo2PvlnHRAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0253ad58d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,6))\n",
    "\n",
    "i=1\n",
    "for title in df['Name'].unique():\n",
    "    fig.add_subplot(3, 6, i)\n",
    "    plt.title('Title : {}'.format(title))\n",
    "    df.Survived[df['Name'] == title].value_counts().plot(kind='pie')\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Miss\n"
     ]
    }
   ],
   "source": [
    "print(df['Name'][2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/karunya-admin/anaconda2/lib/python2.7/site-packages/ipykernel_launcher.py:23: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass Name     Sex   Age  SibSp  Parch  \\\n",
       "0            1         0       3    1    male  22.0      1      0   \n",
       "1            2         1       1    6  female  38.0      1      0   \n",
       "2            3         1       3    5  female  26.0      0      0   \n",
       "3            4         1       1    6  female  35.0      1      0   \n",
       "4            5         0       3    1    male  35.0      0      0   \n",
       "\n",
       "             Ticket     Fare Cabin Embarked  \n",
       "0         A/5 21171   7.2500   NaN        S  \n",
       "1          PC 17599  71.2833   C85        C  \n",
       "2  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3            113803  53.1000  C123        S  \n",
       "4            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "replacement = {\n",
    "    'Don': 0,\n",
    "    'Rev': 0,\n",
    "    'Jonkheer': 0,\n",
    "    'Capt': 0,\n",
    "    'Mr': 1,\n",
    "    'Dr': 2,\n",
    "    'Col': 3,\n",
    "    'Major': 3,\n",
    "    'Master': 4,\n",
    "    'Miss': 5,\n",
    "    'Mrs': 6,\n",
    "    'Mme': 7,\n",
    "    'Ms': 7,\n",
    "    'Mlle': 7,\n",
    "    'Sir': 7,\n",
    "    'Lady': 7,\n",
    "    'the Countess': 7\n",
    "}\n",
    "#df['Name'] = df['Name'].replace(lambda x : replacement.get(x))\n",
    "\n",
    "for jef in range(0,len(df['Name'])):\n",
    "    df['Name'][jef]=replacement[df['Name'][jef]]\n",
    "    \n",
    "#for key in replacement:\n",
    "#    print (key, 'corresponds to', replacement[key])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>-1.264348</td>\n",
       "      <td>male</td>\n",
       "      <td>-0.180285</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.070922</td>\n",
       "      <td>female</td>\n",
       "      <td>-0.783700</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.00</td>\n",
       "      <td>B42</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.070922</td>\n",
       "      <td>female</td>\n",
       "      <td>-0.632847</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>male</td>\n",
       "      <td>-0.255712</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.00</td>\n",
       "      <td>C148</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>male</td>\n",
       "      <td>0.196849</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass      Name     Sex       Age  SibSp  Parch  \\\n",
       "886          887         0       2 -1.264348    male -0.180285      0      0   \n",
       "887          888         1       1  1.070922  female -0.783700      0      0   \n",
       "888          889         0       3  1.070922  female -0.632847      1      2   \n",
       "889          890         1       1 -0.797294    male -0.255712      0      0   \n",
       "890          891         0       3 -0.797294    male  0.196849      0      0   \n",
       "\n",
       "         Ticket   Fare Cabin Embarked  \n",
       "886      211536  13.00   NaN        S  \n",
       "887      112053  30.00   B42        S  \n",
       "888  W./C. 6607  23.45   NaN        S  \n",
       "889      111369  30.00  C148        C  \n",
       "890      370376   7.75   NaN        Q  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "df['Name'] = StandardScaler().fit_transform(df['Name'].values.reshape(-1, 1))\n",
    "df['Age'] = StandardScaler().fit_transform(df['Age'].values.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>male</td>\n",
       "      <td>-0.557420</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.537975</td>\n",
       "      <td>female</td>\n",
       "      <td>0.649410</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1.070922</td>\n",
       "      <td>female</td>\n",
       "      <td>-0.255712</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.537975</td>\n",
       "      <td>female</td>\n",
       "      <td>0.423129</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>male</td>\n",
       "      <td>0.423129</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass      Name     Sex       Age  SibSp  Parch  \\\n",
       "0            1         0       3 -0.797294    male -0.557420      1      0   \n",
       "1            2         1       1  1.537975  female  0.649410      1      0   \n",
       "2            3         1       3  1.070922  female -0.255712      0      0   \n",
       "3            4         1       1  1.537975  female  0.423129      1      0   \n",
       "4            5         0       3 -0.797294    male  0.423129      0      0   \n",
       "\n",
       "             Ticket     Fare Cabin Embarked  \n",
       "0         A/5 21171   7.2500   NaN        S  \n",
       "1          PC 17599  71.2833   C85        C  \n",
       "2  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3            113803  53.1000  C123        S  \n",
       "4            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Fare'].fillna(-1, inplace=True)\n",
    "medians = dict()\n",
    "for pclass in df['Pclass'].unique():\n",
    "    median = df.Fare[(df[\"Fare\"] != -1) & (df['Pclass'] == pclass)].median()\n",
    "    medians[pclass] = median\n",
    "for index, row in df.iterrows():\n",
    "    if row['Fare'] == -1:\n",
    "        df.loc[index, 'Fare'] = medians[row['Pclass']]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2QAAAD7CAYAAAAFMFfDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0225355e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,4))\n",
    "\n",
    "i=1\n",
    "for pclass in df['Pclass'].unique():\n",
    "    fig.add_subplot(1, 3, i)\n",
    "    plt.title('Class : {}'.format(pclass))\n",
    "    df.Survived[df['Pclass'] == pclass].value_counts().plot(kind='pie')\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/karunya-admin/anaconda2/lib/python2.7/site-packages/sklearn/utils/validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    }
   ],
   "source": [
    "df['Pclass'] = StandardScaler().fit_transform(df['Pclass'].values.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2QAAAHUCAYAAABVveuUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0253b06e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,8))\n",
    "i = 0\n",
    "for parch in df['Parch'].unique():\n",
    "    fig.add_subplot(2, 4, i+1)\n",
    "    plt.title('Parents / Child : {}'.format(parch))\n",
    "    df.Survived[df['Parch'] == parch].value_counts().plot(kind='pie')\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "replacement = {\n",
    "    6: 0,\n",
    "    4: 0,\n",
    "    5: 1,\n",
    "    0: 2,\n",
    "    2: 3,\n",
    "    1: 4,\n",
    "    3: 5\n",
    "}\n",
    "df['Parch'] = df['Parch'].apply(lambda x: replacement.get(x))\n",
    "df['Parch'] = StandardScaler().fit_transform(df['Parch'].values.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.drop('Ticket', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.827377</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>male</td>\n",
       "      <td>-0.557420</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.566107</td>\n",
       "      <td>1.537975</td>\n",
       "      <td>female</td>\n",
       "      <td>0.649410</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.827377</td>\n",
       "      <td>1.070922</td>\n",
       "      <td>female</td>\n",
       "      <td>-0.255712</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.566107</td>\n",
       "      <td>1.537975</td>\n",
       "      <td>female</td>\n",
       "      <td>0.423129</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.827377</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>male</td>\n",
       "      <td>0.423129</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived    Pclass      Name     Sex       Age  SibSp  \\\n",
       "0            1         0  0.827377 -0.797294    male -0.557420      1   \n",
       "1            2         1 -1.566107  1.537975  female  0.649410      1   \n",
       "2            3         1  0.827377  1.070922  female -0.255712      0   \n",
       "3            4         1 -1.566107  1.537975  female  0.423129      1   \n",
       "4            5         0  0.827377 -0.797294    male  0.423129      0   \n",
       "\n",
       "      Parch     Fare Cabin Embarked  \n",
       "0 -0.468807   7.2500   NaN        S  \n",
       "1 -0.468807  71.2833   C85        C  \n",
       "2 -0.468807   7.9250   NaN        S  \n",
       "3 -0.468807  53.1000  C123        S  \n",
       "4 -0.468807   8.0500   NaN        S  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sklearn\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    " df['Sex'] = df['Sex'].factorize()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "del(df['Cabin'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['Embarked'] = df['Embarked'].factorize()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.827377</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.557420</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.566107</td>\n",
       "      <td>1.537975</td>\n",
       "      <td>1</td>\n",
       "      <td>0.649410</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.827377</td>\n",
       "      <td>1.070922</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.255712</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.566107</td>\n",
       "      <td>1.537975</td>\n",
       "      <td>1</td>\n",
       "      <td>0.423129</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.827377</td>\n",
       "      <td>-0.797294</td>\n",
       "      <td>0</td>\n",
       "      <td>0.423129</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.468807</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived    Pclass      Name  Sex       Age  SibSp     Parch  \\\n",
       "0            1         0  0.827377 -0.797294    0 -0.557420      1 -0.468807   \n",
       "1            2         1 -1.566107  1.537975    1  0.649410      1 -0.468807   \n",
       "2            3         1  0.827377  1.070922    1 -0.255712      0 -0.468807   \n",
       "3            4         1 -1.566107  1.537975    1  0.423129      1 -0.468807   \n",
       "4            5         0  0.827377 -0.797294    0  0.423129      0 -0.468807   \n",
       "\n",
       "      Fare  Embarked  \n",
       "0   7.2500         0  \n",
       "1  71.2833         1  \n",
       "2   7.9250         0  \n",
       "3  53.1000         0  \n",
       "4   8.0500         0  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#train and test\n",
    "\n",
    "y=df['Survived']\n",
    "del(df['Survived'])\n",
    "X=df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = X.as_matrix().astype(np.float)\n",
    "#X= X.reshape(X.shape[0],1,X.shape[1])\n",
    "y= y.as_matrix().astype(np.float)\n",
    "#y= y.reshape(X.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_test=X[700:]\n",
    "y_tets=y[700:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=X[:700]\n",
    "y=y[:700]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(700, 9)\n",
      "(700,)\n",
      "(191, 9)\n",
      "(191,)\n"
     ]
    }
   ],
   "source": [
    "print(X.shape)\n",
    "print(y.shape)\n",
    "print(X_test.shape)\n",
    "print(y_tets.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(700, 9)\n",
      "(700,)\n"
     ]
    }
   ],
   "source": [
    "from sklearn import preprocessing\n",
    "scaler = preprocessing.StandardScaler()\n",
    "X = scaler.fit_transform(X) #features made unit varient\n",
    "        \n",
    "print(X.shape)\n",
    "    \n",
    "print(y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "    \n",
    "from sklearn import metrics\n",
    "from sklearn import ensemble\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import cross_val_score\n",
    "scores = cross_val_score(ensemble.RandomForestClassifier(), X,y,cv=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "89.7142857143\n",
      "83.2460732984\n"
     ]
    }
   ],
   "source": [
    "from xgboost import XGBClassifier    \n",
    "    #XGB classifier()\n",
    "jeffin= XGBClassifier()\n",
    "jeffin.fit(X,y)\n",
    "print(jeffin.score( X,y, sample_weight=None)*100)\n",
    "print(jeffin.score( X_test,y_tets, sample_weight=None)*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "41.8413486479\n"
     ]
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Train the model using the training sets\n",
    "#y=y.astype(int)\n",
    "#y_tets=y_tets.astype(int)\n",
    "regr.fit(X, y)\n",
    "print(regr.score( X,y, sample_weight=None)*100)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "79.5714285714\n",
      "65.9685863874\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "gn=GaussianNB()\n",
    "gn.fit(X, y) \n",
    "print(gn.score(X, y, sample_weight=None)*100)\n",
    "print(gn.score(X_test, y_tets, sample_weight=None)*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "def plot_roc(y_true,clf):\n",
    "    from sklearn.metrics import roc_curve,auc\n",
    "    false_positive_rate, true_positive_rate, thresholds = roc_curve(y_true, clf['y_pred'])\n",
    "    roc_auc = auc(false_positive_rate, true_positive_rate)\n",
    "    sns.set('notebook', 'whitegrid', 'dark', font_scale=1.5, font='Ricty',\n",
    "        rc={\"lines.linewidth\": 2.5, 'grid.linestyle': '--'})\n",
    "    plt.figure()\n",
    "    plt.plot(false_positive_rate,true_positive_rate,color='darkorange',lw=2,label='ROC curve (AUC=%0.3f)'%roc_auc)\n",
    "    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('False positive rate ')\n",
    "    plt.ylabel('True Positive Rate ')\n",
    "    plt.title('ROC curve for : '+clf['name'])\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    #plt.savefig('./results/roc/'+clf['name']+'.png')\n",
    "    plt.show()\n",
    "    plt.close()\n",
    "          \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pylab as pylab\n",
    "def plot_cm(y, clf, labels):\n",
    "    from sklearn.metrics import confusion_matrix\n",
    "    cm=confusion_matrix(y,clf['y_pred'])\n",
    "    percent = (cm*100.0)/np.array(np.matrix(cm.sum(axis=1)).T) \n",
    "    print ('\\nConfusion Matrix Stats : '+ clf['name'])\n",
    "    for i, label_i in enumerate(labels):\n",
    "        for j, label_j in enumerate(labels):\n",
    "            print (\"%s/%s: %.2f%% (%d/%d)\" % (label_i, label_j, (percent[i][j]), cm[i][j], cm[i].sum()))\n",
    "    fig = plt.figure(figsize=(20,10))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.grid(b=False)\n",
    "    cax = ax.matshow(percent, cmap=plt.cm.Blues)\n",
    "    pylab.title('Confusion matrix : '+ clf['name']+' : '+str(clf['acc'])+'%\\n')\n",
    "    fig.colorbar(cax)\n",
    "    ax.set_xticklabels([' '] + labels)\n",
    "    ax.set_yticklabels(['   '] + labels)\n",
    "    ax.text(0,0,percent[0][0],va='center',ha='center',bbox=dict(fc='w',boxstyle='round,pad=1'))\n",
    "    ax.text(0,1,percent[0][1],va='center',ha='center',bbox=dict(fc='w',boxstyle='round,pad=1'))\n",
    "    ax.text(1,0,percent[1][0],va='center',ha='center',bbox=dict(fc='w',boxstyle='round,pad=1'))\n",
    "    ax.text(1,1,percent[1][1],va='center',ha='center',bbox=dict(fc='w',boxstyle='round,pad=1'))\n",
    "    pylab.xlabel('Predicted')\n",
    "    pylab.ylabel('Actual')\n",
    "    #pylab.savefig('./results/'+clf['name']+'.png')\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_cm(y, clf, labels):\n",
    "    from sklearn.metrics import confusion_matrix\n",
    "    cm=confusion_matrix(y,clf['y_pred'])\n",
    "    percent = (cm*100.0)/np.array(np.matrix(cm.sum(axis=1)).T) \n",
    "    print ('Confusion Matrix Stats : ',clf['name'],'\\t Accuracy ',clf['acc'])\n",
    "    for i, label_i in enumerate(labels):\n",
    "        for j, label_j in enumerate(labels):\n",
    "            print (\"%s/%s: %.2f%% (%d/%d)\" % (label_i, label_j, (percent[i][j]), cm[i][j], cm[i].sum()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import string\n",
    "import time\n",
    "import csv\n",
    "from sklearn import cross_validation\n",
    "def stratified_cv(X, y, clf_class, clf_name, shuffle=True, n_folds=3, **kwargs):\n",
    "    from sklearn.metrics import accuracy_score\n",
    "    stratified_k_fold = cross_validation.StratifiedKFold(y, n_folds=n_folds, shuffle=shuffle) #it will have each folds with index of y. Use this index to get corresponding x values \n",
    "    y_pred = y.copy()\n",
    "    clf = clf_class(**kwargs)\n",
    "    \n",
    "    start_time=time.time()\n",
    "    #Iterate throught the folds. we will have ii part with 90% of train data index and jj part with 10% of test data index.\n",
    "    for ii, jj in stratified_k_fold:\n",
    "        X_train, X_test = X[ii], X[jj]\n",
    "        y_train = y[ii]\n",
    "        clf.fit(X_train,y_train)\n",
    "        y_pred[jj] = clf.predict(X_test)\n",
    "    accuracy = accuracy_score(y_pred,y)*100\n",
    "    print(str(clf_name)+\"\\t\" +\"%.3f\"%(time.time()-start_time)+\"\\t\"+ str(accuracy))\n",
    "    return {'name':clf_name,'y_pred':y_pred ,'acc':accuracy}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier\t Execution Time \t Accuracy\n",
      "Gaussian NB \t0.005\t78.5714285714\n",
      "XGBoost\t0.057\t80.2857142857\n",
      "Lrmodel\t0.002\t63.1428571429\n"
     ]
    }
   ],
   "source": [
    "print(\"Classifier\\t Execution Time \\t Accuracy\")\n",
    "GNB=stratified_cv(X, y,GaussianNB,\"Gaussian NB \")\n",
    "XGB=stratified_cv(X,y,XGBClassifier,\"XGBoost\")\n",
    "\n",
    "Lr=stratified_cv(X,y,linear_model.Ridge,\"Lrmodel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZoAAAEkCAYAAAAWxvdmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzsnXdYVEcXh9+lShFQQYWoWFBABXuL\niMaSWCK2aOwSNbH3WJKY2JJo7Bii5LPEnmiKsReiURMTG8ZgLFHAiAWlqPS+9/tjZZcV0AV22V2Y\n93l8hLllzv3dYc/OzJkzMkmSJAQCgUAg0BEm+jZAIBAIBKUb4WgEAoFAoFOEoxEIBAKBThGORiAQ\nCAQ6RTgagUAgEOgU4WgEAoFAoFOEoxEIcvH48WNmzZqFj48P7u7uDBs2TN8mlTnmzJmDu7u7vs0Q\naBEzfRtQVjl37hzDhw9XK7O2tqZmzZr06tWLoUOHYmaW/+u5cOEC27Zt49KlSzx9+pTy5cvTsGFD\n3n77bTp37lxgnbdv32bLli2cPXuWhw8fIpfLcXZ2pmXLlvTv3x9vb2+tPqMx8sUXX3Do0CHGjh1L\n9erVcXR01LdJL+TGjRts376dCxcu8OjRI7Kzs3F0dKRBgwZ07tyZHj16YG5urm8zjY7cf5+ffvop\n/fv3z3OOu7s7HTp04Ouvv1aWDRs2jPPnz6ud5+DgQI0aNejbty8DBgzA1NRUt8YbIMLR6Jk333wT\nX19fJEkiNjaWvXv3snjxYsLDw1m0aFGe81etWkVQUBCvvPIKb731FtWqVSM2NpYDBw4wYcIEevXq\nxeLFi/M05u+//54FCxZgYWHBm2++iYeHB2ZmZty+fZtjx46xe/duDh48iJubW0k9ukFy5swZfHx8\nmDhxor5NeSlBQUEEBARgZ2dH9+7dqVu3Lubm5jx69Ig//viD2bNnc+nSJRYuXKhvUwvFokWLWLBg\ngb7NULJmzRp69uxJuXLlNDrfwsKCTz/9FABJkoiLi+PgwYPMnz+f8PBw5s6dq0tzDRNJoBfOnj0r\n1atXT9qwYYNaeXJysuTr6yu5u7tLcXFxasd2794t1atXT/L395dSUlLUjmVmZkqzZs2S6tWrJ61e\nvVrt2JkzZyQPDw/pzTfflB4+fJjHlszMTOmbb76Rbt26paWnKx5yuVxKSkrSS93u7u7S7NmztX7f\nxMRErd7vxx9/lOrVqyeNGDFCSkhIyPeca9euSdu3b9dqvWWFnL/Pvn37SvXq1ZOCgoLynFOvXj3p\nvffeUysbOnSo1Lhx4zznpqWlSW3btpWaNm2qM5sNGTFHY2BYW1vTqFEjJEkiMjJSWZ6RkUFAQADW\n1tasWLECKysrtevMzMxYuHAhLi4ubNq0icePHyuPLV++HEmSWLVqFVWqVMlTp5mZGf7+/hr1ZpKS\nkli1ahXdunXDy8uLVq1aMWjQIA4ePKg8Z9iwYXTs2DHPtffu3cPd3Z0vv/xSWXbu3Dnc3d356aef\n2LFjB927d8fLy4tNmzYxdepUGjZsqPYsOURERODu7s5nn32mVn7o0CEGDRpEkyZNaNSoEf379+fI\nkSMvfa4vv/wSd3d3JEliz549uLu7K+3K4fvvv6dPnz54e3vTrFkzRo4cycWLF/Pcy93dnTlz5vDn\nn38qbRk3btwL609NTSU8PJzo6OiX2pqRkcHKlSuxsbFh9erVlC9fPt/zPD09GTJkiFpZzrBghw4d\naNiwIa1atWL8+PHcuHGjwOd4np9++gl3d3fOnTunLHv69Cmff/45nTt3VraLvn37smHDBrVrf/75\nZ9566y2aN29O48aN6dSpEzNmzFB7x/nN0YSHhzN//nx69OihfLd9+/Zl9+7deezLeZcRERGsXLkS\nX19fGjZsiJ+fH6dOncpXq4Lo1q0bDRo0YP369Tx58qRQ1+bG0tISBweHMjuMKYbODJC7d+8CYG9v\nryy7dOkSMTEx9OzZk4oVK+Z7naWlJX5+fgQFBXHq1Cn69OnD3bt3uXr1Ks2bNy/2sFhCQgKDBw/m\n1q1bvPHGGwwaNAi5XM61a9f49ddf6dGjR5HvvWXLFp4+fUr//v1xcnKiatWqeHt7c/jwYQ4dOsTQ\noUPVzt+7dy8Affr0UZblDCu2a9eOKVOmYGJiQnBwMFOmTOGTTz7J86Gbmy5dulCjRg1mzZpF8+bN\nGTBgAABNmzYFYNmyZWzYsAFvb2+mT59OUlISu3fvZsSIEaxdu5b27dur3e+ff/7h6NGjDBgwQM3G\ngggNDWX48OH06dOHJUuWvPDcnLbQu3dvHBwcXnrv3Gzfvh17e3sGDBiAk5MTkZGR7N69m0GDBrFn\nzx5q1qxZqPvlMGXKFC5evMjbb7+Nh4cHqampREREcP78eUaPHg0o3tns2bNp3rw5kydPply5cjx4\n8IDTp08TFxdXYLsGOH/+PBcvXqRDhw5Uq1aN1NRUjhw5wscff8yTJ08YM2ZMnmvmzJmDmZkZI0eO\nJDMzky1btjBhwgSOHDlCtWrVNHoumUzGzJkz8ff3JygoiA8++ECj63I7zsePH7Nnzx5u3brF2LFj\nNbq+tCEcjZ5JTU1VNsqYmBi+++47rl27hpeXF7Vq1VKed+vWLQAaNGjwwvvVr18fgJs3b6pd5+np\nWWxbV65cya1bt1i4cCFvv/222jG5XF6se0dFRXH48GEqVaqkLMvOzsbJyYmff/5ZzdFIksS+ffuo\nV6+e8nmvXr1KUFAQY8aMYfr06cpzhw8fzvjx41mxYgW9evXC1tY23/o9PDzw8PBg1qxZVK9enV69\neimPRUREsHHjRpo2bcqWLVuwsLAAoH///vTo0YMFCxYQHBysNi9269YtvvnmG1599dVi6ZIfL3qn\nSUlJZGRkKH+XyWRUqFBB+fuGDRuwtrZWu6Z379706tWLzZs3M3/+/ELbk5iYyNmzZxk0aBCffPJJ\ngecFBwdjY2PDli1b1AJdpk6d+tI6evXqxaBBg9TK/P39GTFiBP/73/8YOXJknt5ChQoVCAoKQiaT\nAdCqVSv69+/Prl27mDFjhsbP16ZNG9q2bcvOnTsZPnw4r7zyygvPT0lJoU2bNmplpqamTJw4kUmT\nJmlcb2lCOBo98+WXX6oNJQG8/vrref5gk5KSAAr8oMwhZxglMTFR7TobG5ti2SmXyzl06BB16tRR\nftvPjYlJ8UZhe/XqpeZkQPHH2bNnTzZt2kR4eDh16tQBFMNtDx48YPbs2cpz9+/fj0wmo3fv3nmG\n2jp27Mjx48e5fPkyPj4+hbbt+PHjSJLE6NGjlU4GoEqVKvTp04etW7cqvxzk4OHhUSgn06pVK/79\n91+Nzn3RO/3www85evSo8ndra2v++usvtd9B4ayTk5PJyMigQoUK1KpVi9DQUI3tzY2lpSUWFhaE\nhoZy7969AnsL5cuXJy0tjZMnT9KpUyelA9CE3M4xPT2dlJQUJEmibdu2nD9/XjmUmpvhw4er1eHt\n7Y2NjQ137twp5BPC+++/T9++fQkICGDp0qUvPNfS0pKgoCDl77GxsQQHBxMYGIhMJjOKQBNtIxyN\nnnn77bfp2rUrmZmZ3Lx5kw0bNvDw4UMsLS3VzstxMDkfMgWRczzH4eRcl5ycXCw7nzx5Qnx8PO3a\ntSvUB4SmFDRk07t3bzZt2sTevXuVPZW9e/cqnVAO4eHhSJJEt27dCqwjNja2SLbdu3cPgLp16+Y5\nVq9ePUAx3Jnb0RR1CEoTXvROJ0yYwMCBAwFYsmSJchg2h2vXrhEQEMD58+dJSUlRO6bpcNLzWFhY\n8OGHH/LZZ5/RqVMn3NzcaN26NZ07d1b7Zj9mzBguXLjAhAkTcHBwoGXLlvj6+tKtW7eXfoFKTk4m\nMDCQw4cPExUVled4QkJCnrLq1avnKXNwcCjSXEv9+vXp0aMH+/fvZ+TIkXh4eBR4rqmpaZ4vGX5+\nfowePZqvvvqKrl27lrnoTuFo9Iyrq6uyUbZv355mzZoxePBg5s2bx6pVq5Tn5XzIXb169YX3yzme\n8wGYc93169eLZaekhW2LsrOzCzz2fHBDDu7u7nh6erJv3z6mTZtGWloaR48epW3btjg5OanZJ5PJ\nWL9+fYHrFIr6x12UZy/oebTBi95p7m/19vb2ao7mwYMHDBkyBFtbW8aNG0ft2rWxsrJCJpPx+eef\n53E8BZHfexw0aBCdOnXi1KlTnD9/nqNHj7J9+3a6d++ubMc1a9bk0KFD/Pnnn/z555+cP3+euXPn\nsmbNGnbs2EGNGjUKrHPGjBmcPHmSAQMG0KJFC+zt7TEzM+PUqVNs3rw536Hb4vayn2fq1KkcPXqU\n5cuX5wly0AQfHx9+++03zp07JxyNQL80bdqUXr168fPPPzNs2DDlZHTTpk1xdHTk+PHjPH78ON+J\n0/T0dPbv34+lpSW+vr6A4ltd/fr1uXTpktrwU2GpWLEi9vb2+UYnPY+Dg0O+DvH5b9ea0rt3bxYv\nXszZs2eJiYkhOTk5zwR7zZo1+e2333BxcSnyMxZEzgfgrVu38nwYhoWFAfl/e9YVTZs2xcnJieDg\nYObMmaM2B/MigoODSUlJYd26dbRu3Vrt2NOnT9WGBUHxHp8+fZrnPgW9x8qVK9O/f3/69+9PdnY2\ns2bN4sCBA7zzzjvKxcAWFha0b99eGTxx6tQp3nvvPb755hvmzZuX730TEhI4efIkvXr1yrMm6I8/\n/tDo2bVB9erVGTRoEFu3buXs2bOFvj4rKwso/uiCMSLCmw2Q8ePHY2pqypo1a5RlFhYWTJ48mZSU\nFGbOnElaWpraNdnZ2cyfP5/79+8zatQotfmO999/H4Dp06cTExOTp77s7Gw2b96s/NDMDxMTE3r0\n6EFYWBjff/99nuO5v/XXrFmT5ORktTF/uVzO5s2bX/7w+dCzZ0/MzMzYu3cve/fupXz58nTq1Ent\nHD8/P0ARsJDfN+64uLgi1Q2KOR6ZTMbGjRvJzMxUlkdHR/PTTz/xyiuvKIMSikphwpstLCyYNm0a\nycnJTJs2TTkf9zzP98RyenrPl+/evTvfdlGzZk0uX75Mamqqsiw+Pl4t5DvH9tzn5NSV07uKj48H\nyDdMPUe3nHPyI6dn8rzd0dHR+bZFXTJu3DhsbW1Zvnx5oa6TJInjx48D0LBhQ12YZtCIHo0B4urq\nSvfu3dm/fz8XL16kefPmgGI+JzIykg0bNtC9e3d69+7NK6+8oswMcPPmTfz8/PJMNrZt25aFCxey\nYMECunbtSo8ePfD09MTMzIw7d+5w7NgxIiMjOXDgwAvtmjp1KmfPnmXu3LmcOXOGZs2aIUkS169f\nJysri2XLlgEwYMAAvvnmGyZMmMDw4cMxNzfn6NGjLxw6exGVKlWiXbt2HD16lPT0dN566608c1je\n3t5MmjSJL7/8kt69e/PGG29QpUoVoqOjuXr1KqdPn+aff/4pUv21a9dm1KhRbNiwgaFDh9KtWzeS\nk5PZvXs3KSkpLF++vNhpRQoT3gzQr18/oqOjCQgIoHPnzmqZAaKjozlz5gwhISHKIVQAX19frKys\nmDVrFkOHDsXOzo5Lly5x+vRpatSokef9DBkyhJkzZzJixAh69epFQkIC33//PS4uLmqO6b///mPo\n0KF06dKFunXrYmdnR0REBN9++y3VqlVTtt9Ro0Zha2tLixYtcHZ2JiEhgT179iCTydSi/J7H1taW\ntm3bsm/fPsqVK4eXlxf3799n165dVKtWLd9el66oWLEio0aNIiAgoMBzsrKylOH3oHCwx44d49Kl\nS/j4+OSJSCsLCEdjoIwbN46DBw8SEBDAtm3blOUzZ87E19eX7du3s3v3bp4+fYqtrS0NGzZk8uTJ\ndOnSJd/79e/fn2bNmilzne3duxe5XI6LiwutW7dm9erVLx03tre3Z9euXQQFBREcHMwvv/yCjY0N\nderUUQs/rl69Ol999RUrV64kICAABwcHevXqRb9+/V44Wf8i+vTpw6+//gpQ4IfSxIkTadiwIdu2\nbWPr1q2kpKRQqVIl6taty4cfflikenOYOXMmrq6u7Ny5kxUrVmBubk6jRo1YsWKF8oO0pBk3bhwd\nOnRg+/btnDlzhp9++gm5XE6lSpVo0KABS5cupXv37srza9Sowfr161m5ciVBQUGYmprStGlTtm3b\nxqJFi7h//77a/f38/IiOjmbHjh0sXryY6tWrM378eExMTPj777+V51WtWpV+/fpx7tw5fvnlFzIy\nMqhSpQr9+/fn3XffVc5XDRo0iMOHD7Nr1y7i4+NxcHDA09OTuXPn5hnKe55ly5axYsUKTpw4oVzv\nM23aNMzMzDRe26It3nnnHXbu3JlvLxAUC2pnzZql/N3S0hJXV1emTZvGyJEjdRJMY+jIJG3M8goE\nAoFAUABijkYgEAgEOkU4GoFAIBDoFOFoBAKBQKBThKMRCAQCgU4pE1FnISEh+jZBIBAIjJJmzZoV\n+x5lwtGAdsQqDSQnJxc7wWZpQWihQmihQmihQltf0sXQmUAgEAh0inA0ZQxNcpWVFYQWKoQWKoQW\n2kc4GoFAIBDoFOFoBAKBQKBTStzR3Llzh08++QQ/Pz88PT0ZNmyYRtclJibywQcf0KJFC5o1a8aM\nGTOKtIFRWcfZ2VnfJhgMQgsVQgsVQgvtU+KO5tatW5w6dYqaNWsWahfCqVOncu7cOT799FOWLFnC\nP//8w4QJE3RnaCnFxcVF3yYYDEILFUILFUIL7VPijqZjx46cOnWKNWvW5Ls1bn789ddf/P7773zx\nxRe88cYbdOnShWXLlhESElKiGx+VBoq6L3xpRGihQmihQmihfUrc0RRle9XTp0/j6OhIixYtlGXe\n3t5Uq1aN06dPa9O8Uk/ujbvKOkILFUILFUILIDOVjMhzWrudUSzYjIiIoHbt2nnK69SpQ0REhB4s\nEggEglKCJEF8BESdhQdnIeosMzdW4q/7Vfji28laqcIoHE1CQgLly5fPU25nZ8e9e/c0ukfuFa4e\nHh6Aery8s7MzLi4uhIaGKr/RWFtb4+npyZ07d4iNjVWe6+XlRUpKCuHh4cqyGjVq4OTkpFaPvb09\nbm5uhIWFqW1V26xZM2JiYoiMjFSW1alTB2tra65cuaIsc3R0xNXVlevXr5OSkgKAubk53t7ePHjw\ngKioqEI/U86mS6XpmYrznkJCQkrdMxXlPZUrV07t+tLwTMV5T8nJyaXumXLe081/LmKTcBWbhCtU\nyrhFuSd/Q6rKdoCGVRuz5veWaAu9bnw2efJknjx5oraDZH688847WFtb89VXX6mVz5gxg/v37/Pd\nd9+98PqQkBCRgkYgEJQ95NkQd03RW4k6p/g/7hqg/rF/Ld6dSwltGDqoHji3RqrSjDtRcuLiwstO\nrjM7OzseP36cpzwxMRE7Ozs9WGS83LlzB1dXV32bYRAILVQILVQYtRYp0SqHEnUWos5DZpL6OSbm\nUKUpOLcmxaEln263ZNmaa5iaymg9cQxuNSoiA2rWhLg47ZhlFI6mdu3a+SZ3i4iIoHPnznqwyHiJ\njY013j8iLSO0UCG0UGE0WmRnQPTlXE7lnGKu5XnsaoJzK3BurfhXuTGYlePw4VtM6HeI27efAjBq\nVDMqVbLSialG4Wh8fX1Zu3YtFy9epHnz5gBcuXKFu3fv4uvrq2frBAKBQMdIEiRGKibrH55T/B99\nCbLT1c8zt4GqLVROxbkV2FRVO+X+/QSmTt3PDz9cA8DbuwpBQT1o06a6zswvcUeTmprKqVOnAHj0\n6BFJSUkcOXIEgPbt22NlZUWXLl1o0aIFn3/+OQBNmjTBx8eH2bNnM3v2bExMTFi2bBnNmjXj1Vdf\nLelHEAgEAt2SmQwPL+bqrZyF5Id5z6voqXAoLs8cS6X6YPLij/UJEw6xd++/WFubs3BhB6ZMaY2Z\nmW5XupS4o4mLi2PKlClqZTm/Hz9+nGrVqpGdnY1cLlc7Z9WqVSxevJgPP/wQuVzOa6+9xkcffVRi\ndpcWvLy89G2CwSC0UCG0UFHiWkhyeHxTfQgsNlRRnptyFdWHwKq2hHIOGlWRlSVXOpMvvuiMubkp\nK1a8To0a9tp+mnzRa9RZSSGizlQ8ffoUBwfNGmdpR2ihQmihQudapD5WDH8pJ+3PQfpT9XNkpuDU\nSL234uAGz5YnaEp8fBpz557g5s3HHDkyRLm8QVO09dlpFHM0Au0RHq6dcMXSgNBChdBChVa1kGdB\nzBX1IbAnN/OeZ+sCzm1UvZUqTcHcusjVSpLE999fY+rUI0RFJWFqKuPy5Yc0aaKfhKHC0QgEAoG2\nSHqgWmH/8JxiniUrRf0cs3JQuZl6b6V8Na2ZEB7+mIkTD3PkSBgAbdpUIyjoTby9q2itjsIiHI1A\nIBAUhcxUiP5LvbeSeDfveQ5uqp6KS2tw9AZTc52YtHz5H3z88a+kpWXh4FCOL77ozOjRTTExKdyQ\nmbYRjqaMUaNGDX2bYDAILVQILVTkq0U++cCIuawYGsuNhV2uCftWULUVWDuWjOFASkomaWlZDBvm\nzfLlr1O5sk2J1f0ihKMpYzg5OenbBINBaKFCaKHCyckJ0uPh4QX1SLDn8oEhMwFHL/XeSkUPRXkJ\nEROTzL//xuHjo3COs2e3pUOHmvj6GtaCU+FoyhgiAk+F0EJFmdZCng2Pryt7KqkRv2KVcpvn84Fh\nXTnXQsjWULU5WORN9lsiJsslNm36i1mzgjEzM+HGjYlUrGiFpaWZwTkZEI5GIBCUNV6SD8wK1PKB\nUbWVordiV7PQ4cW64J9/ohk79gBnzijmg7p0qU1KSiYVK+omfYw2EI5GIBCUXtTygT1zLvnmA3NV\n9lRuxDvg4TtQER1mQCQnZ7Bw4SlWrjxLVpacKlVsWL26K2+/3aDQ62NKGuFoyhj29iWzEtgYEFqo\nKBVaSJIi6iunp1LEfGBmYWEG52QA3nrre44cCUMmg/Hjm/PZZ51wcDA8O/NDOJoyhpubm75NMBiE\nFiqMUovC5gPLiQZzbPDCfGCGqsXs2W159CiJdet60KqV9tbdlATC0ZQxwsLCDPYPqaQRWqgweC1y\n5wPLyV4cewWkbPXzipEPLAdD0CIrS86XX57jv/+eEhDQDYAOHWpy8eJ7el8TUxSEoylj5N4utqwj\ntFBhcFqkPoaH59XDi/PLB1a5abHzgT2PvrU4f/4+Y8Yc4PJlRe/svfea0aBBZQCjdDIgHI1AINA3\nefKBnYMn/+Y9T5kP7FmPpUqzYuUDMzSePk3jww+PExR0EUkCV1d7AgO7K52MMSMcjUAgKFly8oHl\nRIHpIR+YofHdd/8wdeoRHj1KxszMhBkz2vDxx77Y2Fjo2zStIBxNGaPMLsrLB6GFCp1pkZUGjy4Z\nVD6wl6GPdnHsWDiPHiXTtm111q3rgZeX/hJg6gLhaMoYMTExIt3IM4QWKrSixfP5wB6eU6xhkWeq\nn6fMB9ZKtSCyBPOBvYySaBfp6Vncv59I7doVAFi6tAvt2tVgxIjGRjsP8yKEoyljREZGig/XZwgt\nVBRJi/SEZxP2uVbZP58PDJne84EVFl23ixMnbjNu3EFMTGT8/fdYLCxMcXS05p13muisTn0jHI1A\nIHg5z+UDI+osxF3DkPOBGRqPHiXx/vvBbN8eCoCHhyP37iUoezWlGeFoBAJBXtTygZ1T9FwyEtXP\nyckHVrWVqrdiIPnADAm5XGL9+hDmzDnO06dplCtnxty57Zg5sy0WFqb6Nq9EEI6mjFGnTh19m2Aw\nCC2ekZ1BPbt4uPSlqrfyknxgOLeGyo0NMlVLcdF2u+jTZxf79inCtd94ow5ffdWdOnUqarUOQ6dQ\njubu3btcuHCBJ0+e0Lt3bypVqkRcXBzly5fHwqJ0hOGVdqytS8+6g+JSJrUoIB9Y+ULmAyvNaLtd\n9O3rwfnz9wkI6Er//vUNPgGmLtDI0cjlcubPn88PP/yAXC5HJpPRunVrKlWqxAcffECDBg2YMmWK\nrm0VaIErV66IsN5nlAkt8uQDOwfJUXlOS7WuhVWt9irH8pJ8YKWZ4raLffv+5d69BMaPbwHA8OGN\n6NvXk/LlLbVlotGhUUtau3YtP//8M9OmTaNdu3b07t1beax9+/bs2bNHOBqBQN9IcnhyS723km8+\nsArPTdi35NrV8NLvdHVMZGQ8kycfZu/ef7G0NKVrVzdq166ATCYr004GNHQ0e/bsYdy4cbz77rtk\nZ6s32urVq3Pv3j2dGCcQCF5AUfKBVW0FFeqKCXstkpmZzZo155g37yTJyZmUL2/Bp592xNW1FGy9\noCU0cjSPHj2iSZP8Y7wtLCxISUnJ95jA8HB0NJyFcfrGqLTIyQf28Jyqt1JgPrBcvRUN84EZlRY6\npjBanD17jzFjDhAa+giA/v3rs2rVG7zyip2uzDNKNHI0jo6O3Llzh9atW+c5Fh4ejrOzs9YNE+gG\nV1fD209cXxi0FkkP1BdC6jgfmEFrUcIURouPP/6V0NBH1KrlQGBgd7p3r6tDy4wXjRxNx44dCQoK\nolWrVlSvXh0AmUxGbGwsmzdv5vXXX9epkQLtcf36dTw9PfVthkFgMFoUJR+Ycytw8gZT7UR7GowW\nBsCLtJAkicTEDOzsFHMugYHd2Lr1bz76yBdra/3kZjMGNHI0kydP5syZM/j5+eHl5YVMJmPBggX8\n999/ODo6Mm7cOF3bKdASYphThV60UOYDy9VbKSgfWNWWqp6KjvOBiXahoiAt/v03lvHjDyGTQXDw\nMGQyGe7ujnz2WacSttD40MjRODg48OOPP7Jx40ZOnz5NlSpVyMjIYODAgYwePRpbW1uNKwwLC2PR\nokVcvnyZ8uXL079/fyZOnIip6YtXyF65coVVq1Zx9epVJEmifv36TJs2jUaNGmlct0BQ4qQnwMML\n6r2VUpAPrCyRlpbF4sW/sWTJGTIysqlUyYr//ntKrVqlP3WMttA4UN7W1pYpU6YUK4w5Pj4ef39/\n3NzcWLt2LZGRkXzxxRfI5XKmTZtW4HVRUVG888471K9fny+++AKAjRs3MnLkSPbt28crr7xSZJvK\nGubmonufg9a1eD4f2MNzEHuVF+cDa6VYGKnnfGCiXajIrUVwcDjjxx8iLOwxACNHNmbp0i5UqlQG\nF/sWA40cTffu3Vm1ahXu7u6YNXEaAAAgAElEQVR5joWFhTF58mQOHTr00vt89913pKenExgYiK2t\nLW3btiUpKYnAwEDefffdAntGJ0+eJDk5mcDAQOzsFNEcTZo0oXXr1pw6dYrBgwdr8hgCwNvbW98m\nGAzF1kKZDyxnA68C8oFVbqLeWzHAfGCiXajw9vZGkiRGjdrHN99cBqB+fSeCgnrQrp0ImigKGjma\niIgI0tPT8z2WmprK7du3Nars9OnT+Pj4qDmUHj16sHz5cs6fP0/Hjh3zvS4rKwtTU1O11BDW1taY\nmpoiSVK+1wjy58GDB7i4uOjbDIOgUFpkZ0DM3+rZi0tRPjDRLlTkaFGzpgNWVmZ88kl7pk9vU2YS\nYOqCYueYuHXrlsZzNBEREXlCpF1cXLCysiIiIqJAR/P666+zZs0alixZogw8+Oqrr7C3t6dbt27F\ne4AyRlRUlPhAeUaBWjyfDyzqHDwKgRflA6v6bCMvW+MM9RftAi5ffkhUVCKVKyfg4uLC7NltGTbM\nW8zFaIECHc2OHTvYsWMHoAhlnjZtGpaW6mkU0tLSePjwIa+99ppGlSUkJFC+fN6xaDs7OxISEgq8\nrkqVKmzdupUxY8awbds2AJycnNi4cSMVK2qWBTUkJET5s4eHBwA3btxQljk7O+Pi4kJoaCiZmYoI\nIGtrazw9Pblz5w6xsaoJXC8vL1JSUggPD1eW1ahRAycnJ7V67O3tcXNzIywsjPj4eGV5s2bNiImJ\nITIyUllWp04drK2tuXLlirLM0dERV1dXrl+/royEMTc3x9vbmwcPHhAVpcpZpekz5VCanqk47ykk\nJAQHG3Pq2Dwh9p+DmEZfxCbhChYZz0/YQ6p1TUxeeRXTaq9yM7Eiqda1wcTsuWd6oPdnKsp7ytHC\nUN9TUZ5J07ZXq5Y7M2YcYOPGf7C3t+CHHzqQnJwMwOPHETx+bHzPpK33pC1kUgFjT/v27WPfvn0A\n/P777zRu3DhPz8XCwoK6devi7+9PhQov9/oNGjRg1qxZjBgxQq28Xbt29O3bt8CAgOjoaIYMGYKb\nmxuDBg0CYOfOnVy7do3vvvvupd/EQkJCRB6nZ5R5LXLlA4sJ3Y9TZriG+cBaKMpKKWWxXUiSxM8/\n32Dy5CPcu5eAiYmMSZNa0rdvBXx9W+nbPINAW+2iwB6Nn58ffn5+ALz99tt89tlnxd6nwc7OjsTE\nxDzlSUlJ+fZ0cti4cSPZ2dmsWbNGGRHSunVr3njjDTZt2sTcuXOLZVdZIudbTZlBLR/YOUUkWNoT\nAJSb9ebOB5azj30ZywdW1trFnTtPmTjxMAcO3ASgeXMXvv76TZo2dVb2ZgTaQ6M5ml27dmmlstq1\naxMRoT6BGhUVRUpKCrVr1y7wuoiICNzc3NTCDi0sLHBzc1PrWgrKOPIsiP1HPXvxC/KBZVRqioWr\nr8b5wASlA0mS6NdvNyEhUdjZWfL55x0ZO7Y5pqZi3ZKuKFQwQGpqKpGRkflGoGkSHunr68vGjRtJ\nSkpSDsMdOnSIcuXK0bJlywKvc3Fx4fTp02RkZCg3WMvIyODWrVsazw8JFNy4caP0DJEkRakvhCxk\nPrArISE0q1ZKtCgmpapdFIBcLmFiIkMmk7F8+esEBV1k1ao3cHZWH00pC1qUNBo5mqysLBYuXMhP\nP/2UZ5uAHK5fv/7S+wwcOJBt27YxadIk3n33Xe7evUtgYCD+/v5q8z9dunShRYsWfP755wD079+f\nH374gYkTJzJ48GAkSWLHjh3ExMTw9ttva/IIAmNHLR/Ys3Urifn0ZpX5wJ4NgWkxH5jAOImLS2HO\nnF8AWL9eMR3QoUNNOnSoqUeryhYaOZpNmzZx7Ngx5s2bx8cff8ycOXMwNzfnxx9/JDk5mdmzZ2tU\nmb29PZs3b2bhwoWMHTsWOzs7RowYwaRJk9TOy87ORi6XK39v2LAhGzZsIDAwkFmzZgFQr149Nm3a\nVObGlssEkgTxt9V7K/nmAyuvCCtW5gNrCdZO+d9TUOaQJImtW//m/feDiY1NwcLClHnzOlCtmkjh\nX9IUGHWWm549e/LWW28xdOhQGjRowI8//kiDBg2QJInRo0dTv359ZsyYURL2FomyGFFTEAa5ME/j\nfGAN1VO3VPQAk6IvojNILfREadPi+vUYxo07yKlTihDdDh1qsm5dDzw8Xp6YtLRpURx0HnWWm7t3\n7+Lp6YmpqSmmpqbKORqZTMagQYNYtGiRQTsagQq9/wHl5APLnb04v3xgVk7g0kY1BKaDfGB618KA\nKC1aSJLEJ5/8yhdfnCEzU46jozUrVrzOsGHeyDSMIiwtWhgSGjkaGxsbMjIyAMVCycjISJo2bQqA\nqanpCxdbCgyL0NDQks1rlRLz3AZehpMPrMS1MGBKixYymYz79xPJzJTz7rtNWbKkMxUrWhXqHqVF\nC0NCI0dTt25d7ty5g4+PD82bN2f9+vW4ublhZmZGYGAgbm5uurZToCWezxCgVYqUD6yVwsnoIR+Y\nTrUwMoxZiwcPEomNTcHbuwoAS5d2YdSoJrRtW6NI9zNmLQwVjRxN3759letVJkyYwKBBg+jfvz+g\nSFcQFBSkOwsFhokyH1iu3kp++cDMrMG55bNcYK2NOh+YwLDIzpazbt1FPvroBK+8Up7Ll8diYWGK\no6M1jo5FczIC3aCRo8nJEABQq1Ytjh07xu+//45MJqN58+Y4OYlIH2MhdwbsQpGZrHAkuXsryVF5\nz6vooZ66xbEBmBQ7d6tOKLIWpRBj0+LSpSjGjDnAxYuK3HK+vq4kJKTj6Fj85zA2LYwBjaLOjB0R\ndVZIcuUDU65biQkt8/nABPonISGdjz8+QWDgBeRyiWrV7Fizpiu9e3toPNkv0JwSjTp7Eb/88guB\ngYH8/PPPxTZGoHvu3LmDq+tzmzelPVFM0ufeGfJZPjAlynxgrVSOxcjzgeWrRRnFGLSQJAlf32/4\n++9HmJrKmD69NfPnd6B8ecuXX1wIjEELY+OFjiY5OZmTJ08SFxdHzZo18fX1VR47deoUAQEBXLt2\njcqVK+vcUIF2iI1+iKvVk5fnA7NxfhZe/MyplMJ8YLGxseID5RnGoIViu5LWrF17ka+/fpPGjavq\npB5j0MLYKNDR3L17lyFDhhATE4MkSchkMl599VUCAwOZPXs2wcHB2NjYMHXqVPz9/UvQZEGhUMsH\ndo7GD87B6TT1c57PB1a1lSIfmBH3VgTGT0ZGNitX/ompqYyZM9sCMHx4I4YO9RYJMI2MAh3N6tWr\niY+P57333qNhw4bcu3ePjRs38vbbb3Pz5k0GDBjA9OnTcXBwKEl7BS8iJx/Yw3OqYbDn8oGZAjjU\nUZ9bEfnABAbGb7/dYezYg1y7FoOlpSnDhzeiShVbZDIZpqbiC5CxUaCjOXfuHOPGjWPs2LHKsrp1\n6zJ69GiGDh0q9oAxBBLuwv3fCpUPLKNSYyzsX9GPvQaGl5eXvk0wGAxFi9jYFGbNCuabby4DULdu\nRdau7UGVKpptF68NDEWL0kSBjubx48d5og1ysgG88cYburVK8HIeXoSdrRQRYkpk4Oj1wnxgKU+f\nIvouClJSUpTbTpR19K2FJEls3nyZmTODiYtLxcLClA8+8GHOHB/KlSvZ8Hh9a1EaKfANyuVyLC3V\nozlyfhdx5gbA30EKJ1O1Bbj1fjZh3xwsX5yZNjw8XIR6P0NoocIQtNi+/Qpxcal07FiLtWu74+7+\n8gSYusAQtChtvPCrwt9//62Wxywndf/ly5d58kQ9/NXHx0cH5gnyJTMFbu5W/NxtG1R01689AkER\nSEnJJD4+DWfn8shkMtau7c6FCw8YMsRLrIkpZbzQ0eRsPPY8ixYtUjaEnIg0TTY+E2iJsD2KxJTO\nrYWTERglhw/fYsKEQ9SuXYHg4GHIZDLc3R311osR6JYCHc369etL0g5BYfhns+L/Bv6FvrRGDZED\nKgehhYqS0uL+/QSmTj3KDz9cA6B8eUvi4lK1kjpGW4h2oX0KdDTt2rUrSTsEmpIQCZHHwdQS3Au/\njbXIS6dCaKFC11pkZ8v56qsLzJ17gsTEDGxszFm48DUmT26FmZlhrYkR7UL7GNYbFryca9sACdz6\nQLnCr2EKCQnRvk1GitBChS61kMsl2rffzJQpR0hMzKB3bw+uXZvA9OltDM7JgGgXusAw0+oK8keS\n4Opmxc8NRujVFIFAU0xMZLz+eh0iI+MJDOyOn5+YVyxrCEdjTDz4A56Gga0LuHbRtzUCQb5IksTu\n3VcxMzOhX7/6AMye3Zbp09tgayvWp5RFhKMxJq5uUfzvOUxtEWZhsLe316JBxo3QQoW2tAgPf8z4\n8Yc4diwcJydrOnasRYUKVlhammGp3STLOkO0C+0jHI2xkJkC/+5S/FyMYTOx7bYKoYWK4mqRnp7F\nsmV/8Nlnv5GWlkWFCuX47LOO2NuX/BbdxUW0C+1jeDNxgvwJ+xkyEhRpZSp5Fv02YWFaNMq4EVqo\nKI4WJ0/+R+PGX/Pxx7+SlpbFsGHe3LgxkXffbYaJifEtvBTtQvto7Gj+++8/Zs+eTceOHWnSpIly\ngebatWs5f/68zgwUPEMZBOBfrNvEx8cX25TSgtBCRVG1yM6WM378QW7ciMXdvRInTgxn69Y+VK5s\no2ULSw7RLrSPRo7m+vXr9O3bl99//52GDRuSlpamTEeTmJjIzp07dWpkmSfhLtz5pchrZwQCbSKX\nS6SkKLKEm5qasG5dDxYu7MDff4/ltddq6dc4gUGi0RzN8uXLqVevHps2bcLCwoKGDRsqj3l7e3Ps\n2DGdGSgArm8HJKjTC8pV0Lc1gjLMlSuPGDv2IB4eldi4sRcA7dvXpH37mvo1TGDQaORoLl26xLJl\ny7C2tiY7O1vtmKOjI7GxsToxToD62pmG/sW+nchKq0JooeJlWiQnZ7Bw4SlWrjxLVpac27ef8ORJ\nKhUqWJWQhSWHaBfaR+M5GnNz83zL4+Pj82wnINAiUWfhyU2wcdbK2pmYmBgtGFU6EFqoeJEW+/f/\nS/36a1m69I9nczLNuXZtQql0MiDahS7QyNF4enpy5MiRfI8dP368UDvShYWFMWLECBo1aoSPjw8B\nAQF5ekkFcezYMfr164e3tzetWrVi1KhRpKSkaFy3UZLTm6k/DEyKH40eGRn58pPKCEILFflpkZUl\np1+/3fj5fUdkZDyNG1fl7NnRfPVVDxwcjC9sWVNEu9A+Gn1yjRw5kokTJwLQs2dPAP7991+OHDnC\nvn37+N///qdRZfHx8fj7++Pm5sbatWuJjIzkiy++QC6XM23atBde+/3337Nw4UJGjx7NrFmzSEhI\n4OzZsxo7KaMkMxVufKf4WaScEZQwZmYm2NtbYmtrwaJFrzFxYkuDzE0mMAIkDdmxY4fUpEkTycPD\nQ3J3d5fc3d2lxo0bS99++62mt5CCgoKk5s2bS4mJicqy//3vf5K3t7da2fPExcVJjRs3lnbt2qVx\nXbm5ePFika7TO9d2StJyJGl7C63d0mi10AFCCxU5Wpw9e1c6e/ausjw2Nlm6ezdeX2bpBdEuVGhL\nC43HYgYPHoyfnx8XL14kNjaWChUq0KJFC+zsXrx1cG5Onz6Nj48Ptra2yrIePXqwfPlyzp8/T8eO\nHfO97vDhwwD07t1b47pKBdeepZwp5tqZ3NSpU0dr9zJ2hBYqHB2rMW7cAb7+OgQPD0cuXx6LhYUp\nlSoZzj4xJYVoF9pHo37w06dPAbC1taVDhw689dZbdOrUqVBOBiAiIoLatWurlbm4uGBlZUVERESB\n14WGhlKrVi1++OEHfH19adCgAf379+fSpUuFqt+oSLwPd4LB1ALcB2rtttbWZe+DoyCEFooEmDt3\nXqFVq20EBYVgamqCn5872dlyfZumN0S70D4aORofHx8mT57MyZMnlQs1i0JCQgLly5fPU25nZ0dC\nQkKB18XGxnL79m3WrVvH+++/z7p167CysmL06NGlN7T62jaQ5Iq1M1YVtXbbK1euaO1exk5Z1+LW\nrThef307Q4b8xKNHybRtW52//hrDkiWdsbLKP8q0LFDW24Uu0GjobNSoUezfv59jx47h6OiIn58f\nffr0oW7duoWuUCbLm/tIkqR8y3OQy+WkpKQQEBCAr68vAE2bNuW1115j+/btTJ069aX15t7MyMPD\nA4AbN24oy5ydnXFxcSE0NJTMTMWqZ2trazw9Pblz546aQ/Py8iIlJYXw8HBlWY0aNXByclKrx97e\nHjc3N8LCwtTSWjRr1oyYmBi16JY6depgbW2taOSSRIOQIMoBNPDn+vXryug6c3NzvL29efDgAVFR\nUYV+phxK/Jme4ejoiKurq1afqTjvKSQkpNQ9kybvKSLiP3r1OsGjR2lUqFCOCRPq4edXnfT0u4SE\n3DXKZ9Lme0pOTi51z1SU96Q1CjOh88cff0gzZ86UGjduLHl4eEj9+vWTduzYIcXHazZZ2Lp1a+nL\nL7/MU964cWNp/fr1BV43ZcoUqV69elJaWppa+YgRI6SJEye+tF6jm9y7/6ciCGBdVUnKztTqrY1O\nCx1SFrWQy+XKn7dsuSz5+/8sRUcnlUktCkJooUJbWhQqVrFNmzYsXbqUM2fO8Omnn2JlZcWiRYto\n166dRtfXrl07z1xMVFQUKSkpeeZuclOnTh1kMhmSJD3vJF/YEzJactbOeA7VytqZ3Dg6Omr1fsZM\nWdLi0aMkhg3bw6efnlaWDR/eiG++6YWTk02Z0uJlCC20T5GC4q2trfH19cXX15fKlSuTkZGh0XW+\nvr78/vvvJCUlKcsOHTpEuXLlaNmyZYHXdejQAUmSOHfunLIsMTGRq1evKruDpYasNPhXd2tnXF1d\ntX5PY6UsaCGXS3z99UU8PL5i+/ZQVq48S2Jiep7zyoIWmiK00D6FcjQZGRkcPnyY9957j9dee43V\nq1fj5ubGihUrNLp+4MCBWFhYMGnSJP744w927dpFYGAg/v7+aiHPXbp04cMPP1T+7uXlRadOnfjo\no4/Ys2cPJ0+eZNy4cZiZmTFkyJDCPILhE7YX0uOhSnNwbPjy8wtJzvYOgtKvxd9/P6Rt202MHXuQ\np0/T6NrVjZCQ9yhfPm/KqNKuRWEQWmgfjcZlQkND2bNnD4cOHSI+Pp5atWoxefJkevXqRZUqVTSu\nzN7ens2bN7Nw4ULGjh2LnZ0dI0aMYNKkSWrnZWdn54luW7ZsGUuXLmXJkiWkpqbStGlTtmzZUvq2\nXdXSvjMFUepT9hSC0qpFZmY2H3xwnNWrz5KdLeHsbEtAQFfeeqt+gUPNpVWLoiC00D4aOZoBAwZg\nZ2dH165d6du3L40bNy5yhW5ubmzduvWF55w4cSJPmY2NDQsWLGDBggVFrtvgSbwPd44p1s54aG/t\njKBsYWZmwl9/PUQul5g0qSWLFr1mlFsqC0oPGjmaFStW0KVLFywsLHRtT9nm+nbF2pnaPcGqkk6q\nKCgLd1mkNGkRGRlPdracWrUqIJPJCArqQXx8Os2bu2h0fWnSorgILbSPTHo+lKsUEhISYvh7TEgS\nbG4Aj69D7/1Q5019WyQwAjIzswkIOMe8eSdp06YawcHDSmckpkAvaOuzs8Aezfr16+nduzdOTk6s\nX7/+hTeRyWSMHj262MaUaR5eUDgZ6ypQ8w2dVfPgwQNcXDT7llvaMXYt/vzzLmPHHiQ09BEAFSta\nkZKSiY1N4UcejF0LbSK00D4FOpoVK1bQqlUrnJycXhpVJhyNFsi9dsZUd133qKgo8Uf0DGPV4smT\nVObM+YX//U+R669WLQe++qo73boVPlNHDsaqhS4QWmifAh1NaGiock4mNDS0xAwqk2SlwY1vFT+L\nfWcELyA9PYvGjb8mMjIec3MTZs58lY8+8sXaWswrCAyXAh1N7on/xMREHBwcMDU1zXOeXC7nyZMn\nVKqkm8nrMkH4Pkh/CpWbgpPmu5UKyh6WlmaMGtWE48dvs25dD+rXd9K3SQLBS9E4e/PVq1fzPXbt\n2jV8fHy0alSZQ8drZ3JT6jIpFANj0CItLYt5835l505VIsUPP2zHyZMjtOpkjEGLkkJooX00Cm9+\nUWBadna2iHIpDklR8N9RMDEHj0H6tkZgQAQHhzN+/CHCwh5TubINffp4YGVlLrZTFhgdBbbY1NRU\n4uLilKmv4+PjiYuLU/t3//59Dh06RMWK2tsvpcyRs3amTk+w1n0yv9wpwss6hqrFw4dJDB78I6+/\nvp2wsMc0aODEjz8O0OkeMYaqhT4QWmifAns0Gzdu5KuvvgIUUWXvvfdegTfx9/fXumFlAkkq0WEz\ngWGTnS3n669D+PDD48THp2NlZca8ee2ZNq0NFhZ550cFAmOhQEfTpk0bZUDAypUrGTx4MFWrVlU7\nx8LCgnr16vHqq6/q1srSyqOLEHcNrCtDza76tkagZ7KzJb788jzx8el0716XwMBu1KpVQd9mCQTF\npkBH06xZM+WK0MTERIYOHVqoBJoCDfhns+J/zyE6XTuTG2dn5xKpxxgwBC0SE9PJzpZwcCiHhYUp\n69f35NGjJPr29SzRuU9D0MJQEFpoH5GCRl9kpcPXzpD2BIb/DU7e+rZIUIJIksSePTeYPPkwb7xR\nh40be+nbJIEgDyIFjbETsV/hZCo3KVEnExoaire3cGqgPy3+++8pkyYd5sCBmwD8808MaWlZlCun\n3d1UC4NoFyqEFtpHpKDRF3oKAsjMzCzR+gyZktYiMzOblSv/ZMGCU6SmZmFnZ8nnn3dk7NjmmJrq\nN2RZtAsVQgvtI1LQ6IOkKLh95NnamcH6tkZQAqSkZNK69QauXIkGYODAhqxc+TrOzuX1bJlAoHs0\nSkEj9qHRMtd3gJRdYmtncmNtbV2i9RkyJamFtbU5zZu7kJKSydq1PXj99TolVrcmiHahQmihfTQa\nFI6KiiI5ORk3NzcAsrKy2LRpEzdu3MDX15fevXvr1MhShZ7Xznh6epZ4nYaKLrWQJImtW/+mTp2K\n+PjUAGDVqjewsDDV6cLLoiLahQqhhfbRaGB4/vz5fPvtt8rfg4KCWLlyJefPn+eDDz7g559/1pmB\npY7oSxB3FaycoFb3Eq/+zp07JV6noaIrLa5fj+G117bg77+X997bT0ZGNgD29uUM0smAaBe5EVpo\nH40czdWrV2nZsqXy9++//54xY8bw+++/M3jwYHbs2KEzA0sdelg7k5uclEIC7WuRmprJ3LknaNQo\niFOn7uDkZM0HH/hgbm74uclEu1AhtNA+Gg2dxcfHK7cBuH37NtHR0fTqpYj779y5M/v27dOdhaWJ\nrHS4sVPxs0g5U6o4ciSMCRMOERHxBIB3323KkiWdqVjRSs+WCQT6RyNHY29vz+PHjwG4cOECFStW\npHbt2oBiP5qsrCzdWViaiDgAaY/BqTFUbqRvawRaIikpg2HD9hAbm0LDhpUJCupB27Y19G2WQGAw\naORomjZtyqZNm7CxsWHLli34+voqj925c0ekptEUZRCA/nbR9PISG6vlUBwtsrPlyOUS5uam2Npa\nEBDQlXv3Epg2rTXm5saXAFO0CxVCC+2j0eDx9OnTiY6OZtSoUaSmpjJ+/HjlsaNHj9KkSROdGVhq\nSH4Etw+DiRl46m/tTEpKit7qNjSKqkVIyANatdrAkiW/K8sGD/Zi1qy2RulkQLSL3AgttI9GjqZm\nzZqcOHGCU6dO8csvv1C9enXlsRkzZjBt2jSdGVhqyFk7U6uHIluznggPD9db3YZGYbVISEhnypTD\ntGy5gZCQKLZtCyUzM1tH1pUsol2oEFpon0IlV8pviEzkBNIASYKr3yh+FkEARockSfzwwzWmTDlC\nVFQSpqYypk9vzYIFrxltD0YgKEk0djR3795l3bp1nDt3jqdPn+Lg4ECbNm0YO3Ys1apV06WNxk/0\nXxD7D1g5Qu2SXzsjKDqJiem8/fYPHD4cBkCrVq8QFPQmjRtXfcmVAoEgB40cTXh4OAMHDiQtLY2W\nLVtSuXJloqOj2bdvH8HBwXz77bfKKDRBPuQEAXgOAVP9pvOpUUNEQ+WgiRa2thakp2djb2/JkiWd\nee+9ZpiYlNw+MSWFaBcqhBbaRyNHs2LFCipUqMCWLVvUNgV6+PAhI0aMYOXKlQQGBurMSKMmOwOu\nP1s7U19/0WY5ODk56dsEg6EgLU6fvoOzsy1161ZCJpOxaZMf5cqZUaWKbQlbWHKIdqFCaKF9NAoG\nuHDhApMmTcqz81zVqlWZMGEC58+f17jCsLAwRowYQaNGjfDx8SEgIIDsbM0nVOVyOX379sXd3Z1f\nf/1V4+v0RsRBSItT7DlTubG+rSEkJETfJhgMz2sRG5vCyJF7ad9+M+PGHSRnT0BXV4dS7WRAtIvc\nCC20j0Y9mvT0dOzs7PI9Zm9vT3p6ukaVxcfH4+/vj5ubG2vXriUyMpIvvvgCuVyuceTa999/z6NH\njzQ61yDInUCzBLfmFWiOXC6xefNlZs4M5vHjVCwsTGnXrgbZ2RJmZuKdCQTFRaMejZubG3v27Mn3\n2I8//qjM6vwyvvvuO9LT0wkMDKRt27YMGjSICRMmsHnzZpKSkl56fXx8PKtWrWLq1Kka1ad3kh8p\nejQmZor5GYHBcfVqNB06bGbUqH08fpxKp061uHJlHPPmdcDMzPBzlAkExoBGf0kjR47kyJEjDB06\nlF27dnH8+HF27drFkCFDCA4OZtSoURpVdvr0aXx8fLC1VQ1D9OjRg7S0NI2G3wICAmjatClt2rTR\nqD69c2Pns7Uz3fW6diY39vb2+jbBYDAxsaJ164389lsklSvbsH17H4KDh1GvXiV9m1biiHahQmih\nfTQaOnvzzTdJTEwkICCAefPmKcsrVqzIwoUL6d5ds5DdiIgIWrdurVbm4uKClZUVERERdOzYscBr\nb9y4wU8//cTevXs1qkvvSBL8k7N2Rv9BADlo2vsszUiShEwmo0mT+syeHcv9+wl8/nknKlQouwkw\nRbtQIbTQPhqvoxk0aIiWqoQAACAASURBVBD9+/fn5s2bxMfH4+DgQN26dTEz03zNZ0JCAuXL5926\n1s7OjoSEhBde++mnnzJ48GBcXV25d++exnXmkHuCz8PDA1A4rxycnZ1xcXEhNDRUuWe4tbU1np6e\n3LlzRy11uJeXFykpKWoriGvUqIGTk5OyHqvEG9SPvQLlKhEmeRCfq/5mzZoRExNDZGSksqxOnTpY\nW1tz5coVZZmjoyOurq5cv35dmRbD3Nwcb29vHjx4QFRUVKGfycTEhCZNmhTpmUDxbc/NzY2wsDDi\n4+MN4pk0fU/R0amsXXubAQO8qV9fkQi2a1drHBxcqFDByiifSVvvKTo6msTExFL1TKXxPZX0M2kN\n6SU8efJEunbtmvTw4cOXnfpS6tevL23evDlPuY+Pj7Ry5coCrztw4ID06quvSomJiZIkSdLdu3el\nevXqSSdOnNCo3osXLxbN4OJwYookLUeSjk8q+bpfgF600DOZmdnS6tV/Sra2n0swX6pVa7WUlZVd\nJrUoCKGFCqGFCm1pUWB3JDMzk7lz57J//35lmGezZs1YvXo1jo5F2+fezs5O7VtTDklJSfn2dHLs\nWLp0Ke+++y5yuZyEhARl4EBqaipJSUlqcz4GQXaGIrcZiJQzeubChfuMHXuQS5cU3+x69/ZgzZqu\nmJqKiX6BoKQo0NHs2LGDvXv30qhRI7y8vLh79y6nT59m7ty5BAUFFamy2rVrExERoVYWFRVFSkpK\ngZkFUlNTefjwIYsXL2bx4sVqx6ZNm0aNGjUIDg4ukj06I+IQpMaCoxdUFpmt9UFycgazZ//C2rUX\nkCSoUcOeL7/shp+fu75NEwjKHAU6mp9++gk/Pz+WLl2qLNu6dStLliwpci/C19eXjRs3ql1/6NAh\nypUrp7ZVdG6sra3ZunWrWllsbCzTp09n+vTpeYILDAIDXjvTrFkzfZtQIpiZmfDLLxGYmMiYPr0N\n8+a1x8ZGPf1PWdFCE4QWKoQW2qfA8YN79+7Rs2dPtbKePXsil8t58OBBkSobOHAgFhYWTJo0iT/+\n+INdu3YRGBiIv7+/muPq0qULH374IQBmZma0atVK7V+jRordKevVq6f82WBIiYHbB0FmapBrZ2Ji\nYvRtgs4ID39MXJxiQtTS0oxt2/rw119jWLq0Sx4nA6Vbi8IitFAhtNA+BTqalJSUPPHkOdkBcqIT\nCou9vT2bN28mOzubsWPH8uWXXzJixAgmT56sdl52djZyubxIdeidGztBngW1uoGN4e08mjuKpbSQ\nnp7Fp5+epmHDdcye/YuyvEWLV/DyKvgdlEYtiorQQoXQQvu8MDY5MzOTjIwM5e85OcmysrLUygEs\nLDTLSuzm5pZnKOx5Tpw48cLj1apV499//9WovhLnn82K/0UQQIlw8uR/jBt3kBs3FKGlWVlysrPl\nYrJfIDAgXuhohg4dmm/5wIED1X6XyWRcu3ZNe1YZK9GXIeYylKsItd/UtzWlmujoZGbODGbr1r8B\ncHevxLp1PXjttVp6tkwgEDxPgY7m3XffLUk7SgdXtyj+9xgMZpb6taUA6tSpo28Tik1sbAqenl/x\n+HEqlpamfPRRO2bNaoulZaE2jC0VWmgLoYUKoYX2KfAvc8aMGSVph/GTnQHXtyt+NqCUM89jbW2t\nbxOKjaOjNb16uXPvXgJr1/bAza1ike5TGrTQFkILFUIL7SMGsrXF7cOKtTOVGkAVww2PzJ2+wlhQ\nrIkJ5vRpVUqMtWt7cPTo0CI7GTBOLXSF0EKF0EL7FG6sQVAwOcNmBrh2xpjZv/9fJk48TGRkPAcP\n3iI0dBwmJjLKlRNNVyAwFsRfqzZIiYGI/Qa7dsYYuXs3nilTjrBnjyIBYJMmVfn66zcxMRFOXCAw\nNoSj0QY3vlWsnandA2ydX36+HilqnrqSIitLzpo15/jkk19JTs7E1taCTz99jQkTWmp9IzJD16Ik\nEVqoEFpoH+FotEHulDMGjqurq75NeCEJCeksXvw7ycmZ9OvnyerVXalWLf9txIuLoWtRkggtVAgt\ntI8IBigu0X9D9F9QrgLU7vny8/XM9evX9W1CHp4+TSM9XbE/TMWKVnz99ZscODCIH34YoDMnA4ap\nhb4QWqgQWmgfjR1NRkYGP/74I3PmzGHMmDHKNA0nT57k7t27OjPQ4Ln2LAjAfZDBrp3JTc7mSIaA\nJEns3HkFd/dAli49oyzv29eTHj3q6bx+Q9JC3wgtVAgttI9GQ2ePHz/G39+fmzdvUqFCBZ4+farM\nT3bkyBHKlSvH/PnzdWmnYZKdqdp3pqG/Xk0xNm7ejGP8+IMcP34bgNOnI5VbLAsEgtKFRj2aZcuW\n8eTJE3bv3s1vv/2m3AgNoHXr1ly4cEFnBho0/x2BlGioVB+qNNe3NRphbm6u1/rT0rJYsOAkXl7r\nOH78NhUrWrFxox9Hjw4tcSejby0MCaGFCqGF9tGoR3Py5ElmzpyJt7e3MrFmDlWqVOHhw4c6Mc7g\nMeB9ZwrC29tbb3U/fJiEr+833Lr1GAB//8YsW9YFR0f9rMTWpxaGhtBChdBC+2jUo0lOTsbZOf+w\n3czMzDzOp0yQEgvh+0FmAp75Jx81RIq6l5A2qFLFhurV7fH0dOTkyRF8800vvTkZ0K8WhobQQoXQ\nQvto5Ghq1KhBSEhIvscuX75c4DbMpZob34I8E2q+YfBrZ3ITFRVVYnXJ5RJff32RmzfjAEWW7507\n+3L58ljat69ZYnYURElqYegILVQILbSPRo6md+/ebNy4kT179pCeng4oIoZ+++03tm3bRr9+/XRq\npEFyLVfKGUEe/v77IW3bbmLs2IOMH39QOa9XpYotFhamerZOIBCUJBrN0YwcOZKrV6/ywQcf8PHH\nHwMwePBgMjMz6d69O0OGlLG0KzFX4FEIWDpAHT99W2NQJCVlMH/+SVavPkt2toSLS3nGjv1/e+cd\nFtW19eEXFFCCgEhRsEYZRIpGBUURe4nYYmI+MRbUGL1GcxWNaHLjtUWxXxQJ9sRuxBJFJBg1lqiJ\nFY0RFTU2ioBUUdqc7w/C4EgRhhmK7Pd55tHZZ5d1fjOcNWefvdeqHAslBAKBZiiWo9HW1mblypV8\n/PHHnDp1ivj4eGrXro2bmxsdO3bUtI0VD0XeGQ+oXqN8bSkhzZs311jfBw6EM3nyER4/TkZbW4vJ\nk51ZsKAbhoYVc3+RJrWobAgt8hBaqJ8ShaBxcXHBxcVFU7ZUDrIzX8k741muplQknjxJZujQQNLT\ns2nTph4BAf1o29ayvM0SCAQVABGCpqT8/TOkxYBJc6jrVN7WlJjw8HC19ZWZma149mJlZci333Zj\n1ao+/P77p5XCyahTi8qO0CIPoYX6KdYdjaOj4xs304WFhanFoApPJdw7ownOnn3EhAlBfPllB0aM\naAnAtGkdytkqgUBQESmWoxk5cmQ+R5OQkMDZs2fR0tKib9++GjGuwvEi/p+8M5Vr74w6efbsBbNm\n/cK6dZcB8Pe/yPDhb/4hIhAIqi7FcjTTp08vsPzly5eMGTOGhg0bqtWoCkv4LsjOgMZ9oJZVeVuj\nEoVtvH0TkiSxbds1pk0LJTY2DR0dbWbM6MjXX3eqtE5GVS3eRoQWeQgt1E+pntHUqFGDkSNHsmHD\nBnXZU7GpRHlnCsPSsuTPTmJiUunefQsjRx4gNjaNzp0bERY2gQULulGzZuWNC6WKFm8rQos8hBbq\np9SLAd555x1iYmLUYUvFJu5PiLkIekbQbGB5W6My165dK3EbY+MaREWlYmqqz/ffD+TEiVHY2ppp\nwLqyRRUt3laEFnkILdRPqTJsJicns3nzZho3bqwmcyowuXtnbIZWur0zr5KZmVmsekeP3qV163rU\nqaOPnl519uwZQr16BtSpU36xydRNcbWoCggt8hBaqJ9iOZr3338/3zx8RkYGMTExyOVy1qxZoxHj\nKgzyrCqzdyYqKgUvr1B27fqTsWPfY8OGnMgH9vbm5WyZQCCorBTL0TRv3jyfo9HT08PKygp3d3ea\nNGmiEeMqDH+HwvNoqG0D9dqVtzWlQl+/4DuS7Gw5a9deYtasYyQnp1OzZnVsbOq81cnICtOiKiK0\nyENooX6K5WhWrlyptgEjIiKYP38+V69epVatWgwZMoRJkyZRrVrhgRavXbvGzp07uXjxIk+fPqVu\n3br079+fcePGoadXBuFN3qK9M7a2tvnKLl+OYsKEIC5cyAmP7u5ujZ9fXxo3Ni5r88qUgrSoqggt\n8hBaqJ83LgbIyMjA3d2dkydPlnqwpKQkPD090dLSwt/fn88//5zNmzezatWqItsdOXKEhw8fMm7c\nONatW8cnn3zC5s2bC112rVZePIO7P+XsnWkxQvPjaZgHDx4ovf/770Scnddz4UIkVla12Lv3Yw4d\n8njrnQzk16IqI7TIQ2ihft54R6Orq0tsbCy6urqlHmzXrl2kp6fj5+eHgYEBHTt2JDU1FT8/P8aN\nG4eBgUGB7caNG4eJiYnifbt27dDT02P27Nk8efIEKysN7mm59c/emUa9Ku3emVeJi4ujUaNGiveN\nGxszenQratXSY+7cLtSqVTEDYGqC17Woyggt8hBaqJ9iLW92dXXl1KlTpR7s1KlTuLq6KjkUd3d3\nXr58yR9//FFou1edTC65t7fx8fGltqtI3oK9M68SGZlG//47OXnyb0XZunX9WbGid5VyMgKBoOwo\n1jOaoUOH4u3tTVZWFj169MDMzCzfA+LiLAi4d+8e7du3VyqztLSkZs2a3Lt3j27duhXb8CtXrqCt\nra3Z7J7xf0H0BdA1hGaDNDdOGZCZmc2KFef4739/JT1dTlxcGufOjQV4ax/2CwSCikGxY50BbN26\nlW3bthVY5+bNm2/sJzk5mVq1auUrNzQ0JDk5uTimABAbG0tAQAADBw4sdLrtdV5NRZ2bb+LVKK31\n6tXD0tKSa9euKdbRN3r4HaZAipU7t6/9pajr4OBAWload+/eVZQ1bNgQMzMzpXGMjIxo1qwZERER\nJCUlKcrbtGlDbGwsDx8+VJQ1bdoUfX19rl+/rigzNTWlUaNG3Lx5k7S0NAB0dHRwdHQkMjJSKeVs\nUef0/ffHmT//KvfupQAwdKg9Xl4tlGytbOf06uekr6+Pra0tDx48IC4urkTndOnSpbfunFT5nJo3\nb67U/m04p9J8Ts+fP3/rzkmVz0ldaEm5cd6LYOfOnW/81Tt06NA3DmZnZ8eMGTMYNWqUUnmnTp0Y\nPHgwU6dOfWMfGRkZjB49mujoaPbt24eRkdEb21y6dIk2bdq8sZ4S8ixY1xCeR4HHWbCsfHl4EhJe\n8OWXR9m48QoATZvWZsmSzgwe3LKcLasYJCYmYmz89i96KA5CizyEFnmodO0sgELvaCIjIzEzM0NH\nRwcPD49SDwQ5dy4pKSn5ylNTUwu803kdSZLw9vYmIiKCHTt2FMvJqMyDozlOprYM6rV/c/0KiFwu\n8dNPt9DR0WbmTFdmzXLlr79EeI1c7t69q5Y/orcBoUUeQgv1U6ij6d69O7t378bR0VFtg7377rvc\nu3dPqSwqKoq0tLRiPWtZuHAhx44dY9OmTTRt2lRtdhXIn9/n/Gs3qlLtnQkPj6NJE2P09KpTp44+\n27cPpmFDI5o3Ny1v0wQCQRWl0FVnxZhRKzFubm6cOXOG1NRURVlwcDA1atTA2dm5yLZr165l27Zt\nLF26lLZt26rdNiVeJsDdA4AW2FaOvTNpaZl8/fUxHB2/Y8mS3xTlvXo1FU5GIBCUK2Waynno0KHo\n6uoyefJkzp49y+7du/Hz88PT01PpoX7Pnj356quvFO8PHTrEihUrGDRoEBYWFly9elXxevbsmfoN\nvbX7n70zPcCwgfr7VzMhIRHY2/uzcOEZMjNzVpQVRpXJHVQMhBZ5CC3yEFqon1JFby4pRkZGfP/9\n98ybN48JEyZgaGjIqFGjmDx5slK97Oxs5HK54v1vv+X8Qt+3bx/79u1Tqrto0SIGDx6sXkMryd6Z\nyMgUpkwJYc+enBVxDg7mBAT0o0OHwp2jmVnlD++vLoQWeQgt8hBaqJ9CV501b94cMzOzYkUE0NLS\n4pdfflG7ceqiRCsn4m/C9y1y9s5MiAKdihlg7/bteNq2XUdKSgb6+jrMmdOZKVPao6NTeMw4UN8q\nkrcBoUUeQos8hBZ5aHzVGUDjxo0xNDQs9SCVCkXemY8rrJMBsLY2wcnJinfe0WH16vdp1EgsxxQI\nBBWTIh3Nl19+qdZVZxUeeTbc3Jrz/wo2bZacnM7s2SeYONEJmawOWlpaHDw4lHfeKX0MOoFAINAk\nZfqMpsLz8BdIjQTjZmDZobytAXJW/wUG/sW//x1CVFQq4eFxhIQMB1DJyWh071ElQ2iRh9AiD6GF\n+hGO5lUUe2c8K8TemXv3Epg0KZgjRyIAaN++PosX9yhVn82aNVOHaW8FQos8hBZ5CC3UT5kub67Q\nvEyEiP2AVrnnncnIyGbhwtPY2flz5EgExsY1CAhw57ffxtCyZd1S9R0REaEmKys/Qos8hBZ5CC3U\nT6F3NK8GXqsS3NoN2enQsAcYlu86+kePkpg37yTp6dl88okDy5f3wsKieMFD38SrgfuqOkKLPIQW\neQgt1I+YOstFsXdmVJHVNEVCwguMjWugpaVF06Ym+Pr2oVkzE7p312AaBIFAICgDxNQZwLNbEHUe\ndGuB9QdlOrRcLrFp0xWaNVvNtm15AS/Hj28rnEw5sHr1amxsbBSvjh07Mn78+ELv8O/cucOUKVNw\ncXHBwcGB3r174+vrqwjZ/jo3b95kypQpdOzYEXt7e1xdXZk5c+ZbP12zadMmRowoeEp6+PDh2NjY\ncO7cuXzH9u3bh42NjSJs/6ts27YNGxubfOWa0jgjIwMfHx9cXFxo1aoVn332GY8fPy6yzePHj5W+\nT6++evfurag3c+bMQusFBQUp6gUHBzNp0iRcXV2xsbHJt4EdYMOGDfki5Jc34o4G8vbOyD4GnXfK\nbtgbT/nXvw5z+nROzokjRyIYMUKzIfzFRrQ8CtOiVq1abNiwAYAnT56watUqxowZQ3BwsFL4+PPn\nzzN+/HhsbW355ptvMDU15c8//2Tt2rWcOnWKLVu28M47ed+n0NBQvLy8aNu2LbNmzcLCwoLo6GiC\ngoLw8PDgwoULmj3hItDk9+L58+esX7+eJUuW5DsWExPDxYsXAQgKCsLFpXTpONShcWFaLFiwgJ9/\n/plZs2ZRu3Zt/Pz8GDNmDIcOHUJPr+DstObm5uzevVup7OXLl4wdOxY3NzdF2cSJE/OlWtm5cydB\nQUF06JC3AjYkJIQnT57QpUsX9uzZU+CYQ4cOZe3atfz++++0a9fujedbJkhVgIsXLxZ+MDtLkgKs\nJGkZkvTodJnY8/x5hjRz5lGpevV5EsyRzM2XStu3X5PkcrnGx3769KnGx6gsFKTFqlWrJGdnZ6Wy\nK1euSDKZTDp48KCiLC0tTerYsaPk4eEhZWRkKNW/efOmZGdnJy1YsEBRFh0dLbVq1UqaMWNGgZ/z\n8ePHS3s6KvHy5UtJkjT7vdi9e7fk5uZW4Hlv3LhRsrGxkUaOHCm1bdtWSk9PVzq+d+9eSSaTSamp\nqfnabt26VZLJZIr36tK4IC2ioqIkW1tbaf/+/Urj2dnZST/++GOx+s0lODhYkslk0tWrV4us17dv\nX2ns2LFKZdnZ2ZIkSVJqaqokk8mkvXv3Ftj2q6++kiZNmlQiuwqiyGtnCRBTZw+PQeoTMG4KVh01\nPtzt2/HY2fnj4/Mb2dlyJkxoQ3j45wwb5lAmKZVfzdhX1SmuFrmZCV/NVhgSEkJsbCxTp05FR0cn\nX/3+/fsTGBjIixcvANizZw+ZmZl4e3sX+Dl37dq1SBtevnzJkiVL6Nq1K/b29nTr1o3ly5crjtvY\n2OTLfrt69WqlX7S501DXrl1jxIgRODo6smHDBrp164aPj0++Mb/44guGDRumeJ+YmMjs2bPp0KED\nDg4ODB06lLCwsCLtBti/fz89e/Ys8LyDgoJo1aoV48aNIzk5mdOnT7+xv8Iorca5FPS9OHPmDJAT\n8DcXCwsLWrduzalTp0pk5+HDh6lfvz4tWxY+exEeHk5ERAT9+vVTKtfWLt4lu1evXpw4cYLExMQS\n2aYpxNRZ7iKAFmWTd6ZRIyNq1KhOy5YWBAT0o337+hofs1zZ5w73g8tn7CZ9YfDhUncTGRkJQP36\neZ/VhQsXMDIywsnJqcA23bt3Z9++fdy4cYO2bdty4cIF7O3tMTExKfH4kiQxceJErly5wsSJE7G3\nt1eaciopXl5eeHh48Pnnn2NoaEhaWhoHDhxAkiTFBfr58+ecPHmSL7/8EsjLbJucnMyMGTMwMTFh\n586deHp6EhoaWmggyrS0NIVje52///6bGzdu8PXXX+Pi4kKdOnU4fPgw3bt3V+m8SqKxXC5XCtz7\nKtnZ2WRlZaGlpUW1ajmxA+/du0fdunWVpkIhJ73yH3/8UWwbU1NTOXXqFKNHjy6yXnBwMHp6evTo\nodq+udatW5OVlcXFixdV7kOdVG1Hk570z94ZwG6kRobIypITEHARDw976tTRR0+vOiEhn2BlZUj1\n6uKGsqKSlZUF5DiZ+fPnY2trq/QHGxMTg6WlZaHtraysAHj69KmifosWLVSy5cyZM/z222/4+/sr\nXYQHDRqkUn8jRozI97B4w4YNhIWF0apVKwBOnDhBRkYGffr0AeCnn37izp07BAUF0bhxYwA6dOhA\nnz592LRpE97e3gWOFR4eTlZWFtbW1vmOBQUFoa2tTZ8+fahWrRq9e/dm//79pKWloa9f8jiDJdH4\nq6++Yv/+/UXWcXZ2ZuvWnJBUycnJBWYBNjQ0LNFy6F9++YX09HT69u1bZL3g4GA6d+6slD6lJNSq\nVQtLS0uuX78uHE25c+tHyHoJDbuBYSO1d//HH0+YMCGIK1eiuXo1mg0bBgCUawBMjWcmfR013FFo\nisK0SExMxM7OTvHe2NiYwMDAYkUyLwpVp0bPnz+PsbGxyr/0X6dLly5K71u0aEHDhg0JDg5WOJrg\n4GCcnZ0xNc1Jmnfu3Dns7OyoX7++wgkDODk58eeffxY6VlxcHAC1a9fOdyw4OBgnJyfMzc0BcHd3\nZ8eOHRw/fjzflFFxKa7GkyZN4pNPPinwWGpqKgYGBvnuXgrruySfa1BQENbW1gWulsslLCyMR48e\nMX369GL3WxDGxsbExsaWqg91UbUdjYbyziQlveTrr4/j738BSYKGDY0YOLDwL1ZZosovxbeVwrSo\nVasWmzdvRi6XEx4ezuLFi5k+fTo7d+5UzJFbWFhw/fr1Qvt+8uQJgOIiamFhoZiCKymJiYlqzZFS\np06dfGXvv/8+Bw4cYNasWTx//pzTp0/zzTffKI4nJCRw9epVJQecS1GJwtLT0wHyOembN29y9+5d\nhgwZQnJyMgDW1taYm5sTFBSkcDS5U1cFTXNlZ2crjkPJNLa0tKRu3YKjbGRkZKCrq6vkQAwNDRV2\nvkpycnKxI9wnJCRw7tw5Jk2aVGS9w4cP88477+T7QVBSdHV1FfqXN1XX0Ty7DZFnQccArNWTOE2S\nJHbvvsHUqT8THZ1K9eraeHm1Z/bszhUmyvL169fFEud/KEyLatWq4eDgAEDLli3R09PD29ubkJAQ\nxZSHk5MTe/fu5eLFiwWmFj9+/Dj6+vrY29sDOdMwAQEBJCYmKi2RLg7F+WWqq6tLZmamUllhUzoF\n/QJv2rQpMTExXLp0icePHyOXy5UefBsZGWFvb8+cOXMKHLswcgNUvn5Bzt0b4uPjk28hQkJCAklJ\nSRgZGSmet8TGxuabuoqNjVV6HlMSjUs6dfbuu+8SHR2db1rv3r17vPtu8fa7/fzzz2RlZeHu7l5o\nHblcTkhICD169KBGjRrF6rcwUlJSSvxd0xRV9yHBX6/mnVHP3pmwsBg8PPYSHZ1Khw4NuHz5MxYv\n7llhnIxANQYOHIi1tTXr169XlPXp0wczMzP+97//KU0lAdy+fZuDBw8yZMgQxcXio48+onr16ixe\nvLjAMX799ddCx3dxcSExMZETJ04UWqdu3brcvXtX8V4ul3P+/PninB6Qs9BBJpMRHBxMcHAwHTp0\nUJrucnFx4eHDh1haWuLg4KD0KmoaqEmTJgBKGxslSeLIkSO0a9eOLVu2KL2WL19OZmYmoaGhADg6\nOqKrq8uxY8eU+pXL5fz6669KTr4kGk+aNInAwMACXwsWLCAwMJC5c+cq6ru6ugJw9OhRRVmuY351\nP0xRHD58GEdHxyLvAC9cuEBMTEyRzqg4yOVyIiMjFc/TypuqeUcjz4YbW3L+X8qQM9nZcqpVy/HX\nrVrVZerU9rRoYcaYMe+hrV3+EaAFpUdLS4vx48czffp0zp07h4uLCzVr1mTZsmWMHz+eESNGMGLE\nCExNTblx4wYBAQHY2Njw73//W9GHhYUFPj4+TJs2jZiYGD788EMsLCyIiYkhODiYCxcuFLp6qWPH\njri6ujJt2jQ+//xzWrRoQWxsLBcvXmTevHkA9OjRgx07dmBra0uDBg0IDAwkNTW1ROf5/vvvs2XL\nFlJTU5k/f77SsUGDBrFr1y5GjBjBmDFjaNCgAYmJiVy7dg0zMzM8PT0L7LNBgwaYmZlx48YN2rdv\nD8Dly5d58uQJ06dPL3BD4dq1awkKCmLIkCEYGRkxatQofH19SU1NxcnJidTUVHbt2sWDBw9YunSp\nShrXr19faRXhq2RkZCjuaHOpW7cuH330EQsXLkSSJExMTPDz88PS0pIBAwYo6vn5+eHv789ff/2l\n1D53lWBhiyZyOXz4MMbGxnTsWPBWi4iICCIiIhRTYn/++Sf6+vqYmJjg7OysqHf//n3S0tJo3bp1\nkeOVFVXT0Tw8DqmPwehdsHJVuZsTJ+4zcWIwa9f2w80tZzHBihW939CqfMl9uCsomRZ9+/bFz8+P\nDRs2KHavt2/fr9dpzwAAGDJJREFUnj179rBmzRrmzZtHamoqVlZWDBs2jHHjxuV7BtS7d28aNGjA\n2rVr+fbbb0lKSqJ27dq0b9+ezZs3Fzq2lpYWa9aswdfXlx9++IFnz55hbm5O//79FXUmTZrEs2fP\n8PX1RUdHh08++QRra+t8e2uK0sLd3R1fX190dXXzrVTS09Njy5Yt+Pr6snr1auLj4zExMcHR0ZFu\n3boV2XevXr04deoUY8eOBXIupgYGBoW2GzBgACtWrODp06eYm5szbdo0TE1N+fHHH9m4cSO6urq8\n9957bNu2DVtbW6W2qmr8uhYF8Z///IeaNWvi4+PDy5cvcXJyYvny5UpRASRJIjs7O1/bI0eOADnO\nvDCysrIIDQ2ld+/eVK9e8KX5yJEj+Pn5Kd5v376d7du3K03zAZw+fZr69eurvNJR3WhJkiSVtxGa\nJl/e6+DhcHM7dJgLLrNL3N/Tp8/58sujbNmSs1lt4EAbDhwY+oZWAkHV5K+//uKjjz7i5MmTal3U\nICic//u//6Nz585MnDixVP3ku3aqSNV7RpOeBHf+CUTXomR7Z+RyifXrL9G8uR9btoShp1eN+fO7\nsnv3RxowVDPcvHmzvE2oMAgt8tCkFi1atMDV1bXYd1flTWX/XoSFhXHv3j2GDx9e3qYoqHpTZ7f2\nQNYLaNAVjBoXu9n9+wkMH76fs2cfAdCrV1PWrOlLs2Yl3+ldnhQWVbgqIrTIQ9NaeHt7K8K4VHQq\n+/ciMTERHx+fYi+7LguqnqNRMe+MoaEet2/HU7euAf/7X28+/tiuTGKTCQRvA02bNi37zcJVlM6d\nO5e3CfmoWo4m4Q5E/paznNn6wzdW//nnCLp0aYyeXnXq1NHn4MGhtGhhhpFR6da3lyevB4Csyggt\n8hBa5CG0UD9V6xmNIu/MENAtPIbQo0dJfPDBbvr02c7SpWcV5S4uDSq1k4GcfQmCHIQWeQgt8hBa\nqJ+q42gkOfyVu3fGs8AqWVlyVqw4h63tGg4cCMfAQBcTk5plZ2MZoGoYlLcRoUUeQos8hBbqp+o4\nmocnIOURGDWB+p3yHT5//jFt265j2rRQnj/P5MMPbQkP/5yJEwsOA19ZeTWnSlVHaJGH0CIPoYX6\nqTrPaJTyzij7199/f0yHDhuRJGjc2Bg/v/dxd5eVvY0CgUDwFlJ1HM2dvTn/FpB3xtnZit69m/He\ne3X5z3/c0NcXDwMFAoFAXZT51FlERASjRo2iZcuWuLq64uvrW2DIhtdJSUlh1qxZODk50aZNG6ZN\nm0ZCQkLxB856AfU7g1ET7tyJp1+/Hdy+HQ/khPg4fHgYCxd2f+udTG5aYoHQ4lWEFnkILdRPmd7R\nJCUl4enpSbNmzfD39+fhw4csXrwYuVzO1KlTi2w7ZcoU7t+/z4IFC9DW1mbZsmV8/vnn7Nixo9jj\np1uPwmfuryxadIb09Gxq1KhOYODHACIApkAgEGiIMnU0u3btIj09HT8/PwwMDOjYsSOpqan4+fkx\nbty4QtOWXrlyhTNnzrBt2zZFjnYLCwuGDBnC2bNn6dChwxvHPnbPlolrU7h95yQAo0e3YsmSnm9o\n9fYRHh4u8tH8g9AiD6FFHkIL9VOmU2enTp3C1dVVyaG4u7vz8uXLQkOk57YzNTVVOBnIWetev359\nTp06Vayxe/j/H7fvJGBra8rJk55s2jQQU1ORbVIgEAg0TZk6moKy0VlaWlKzZk3u3btXonaQE9ai\nqHavUkNPm4ULu3H16gRFSH+BQCAQaJ4ynTpLTk7Ol44VCs/HXZx2r2buK4ozv+Wk4L1+/WoxrX17\nuXTpUnmbUGEQWuQhtMhDaKFeynx5c0GBKCVJemOAysLaFQcx3yoQCATlR5lOnRkaGpKSkpKvPDU1\ntcA7llfbFXTHk5KSUqFCYQsEAoEgP2XqaN599918z1SioqJIS0sr8BnMq+3u37+fr7ywZzcCgUAg\nqDiUqaNxc3PjzJkzpKamKsqCg4OpUaMGzs7ORbaLjY3l4sWLirLr16/z6NEj3NzcNGqzQCAQCEqH\nllTcBx1qICkpCXd3d6ytrRk3bhyPHj3Cx8eHkSNHKm3Y7NmzJ05OTixcuFBRNnbsWP7++2+8vb3R\n1tZm6dKl1KlTp0QbNgUCgUBQ9pSpo4GcEDTz5s3j6tWrGBoa8tFHHzF58mSqVaumqNOtWzecnZ3x\n8fFRlCUnJ7No0SKOHj2KXC6na9eufP3115iYVK5UygKBQFDVKHNHIxAIBIKqRaXOR1NuATorIKpo\nce3aNWbNmkXPnj1p2bIlvXv3xs/Pj/T09DKyWjOo+r3IRS6XM3jwYGxsbDhx4oQGLdU8pdEiNDSU\nDz/8EEdHR9q1a8fYsWNJS0vTsMWaQ1Utrl+/zpgxY2jXrh3Ozs54enoSFhZWBhZrjgcPHjB79mwG\nDBiAra0tI0aMKFY7Va+dlTZNQHkH6KxIqKrFkSNHePjwIePGjaNRo0bcunULX19fbt26xerVq8vw\nDNRHab4XuezZs4eYmBgNW6p5SqPFnj17mDdvHp9++ikzZswgOTmZ8+fPl8hhVyRU1SIqKorRo0fT\nokULFi9eDMDGjRsZM2YMBw8exMrKqqxOQa3cuXOHkydP0rJlSzIzM4vdTuVrp1RJCQgIkNq2bSul\npKQoytatWyc5Ojoqlb3O5cuXJZlMJv3xxx+KsrCwMEkmk0m//fabRm3WFKpqER8fn69s165dkkwm\nkx4/fqwRWzWNqlrkkpiYKLVr10768ccfJZlMJh0/flyT5mqU0nwvWrVqJe3evbsszCwTVNVix44d\nUvPmzaWkpCRFWWJiotS8eXNp+/btGrVZk2RnZyv+P3nyZGn48OFvbFOaa2elnTorzwCdFQ1VtSho\nIYWtrS0A8fHx6je0DFBVi1x8fX1p3bo1Li4umjSzTFBViyNHjgAwaNAgjdtYVqiqRVZWFtWqVUNf\nPy8Ar76+PtWqVSt2ZJKKiLZ2yS/9pbl2VlpHU54BOisaqmpREFeuXEFbW7vSboQtjRbh4eHs27cP\nb29vTZpYZqiqxbVr12jSpAmBgYG4ublhZ2fHkCFDuHz5sqZN1hiqatGrVy9q1qyJj48P8fHxxMfH\ns2jRIoyMjHj//fc1bXaFojTXzkrraDQRoLOodhUZdZ1TbGwsAQEBDBw4sNDcQBWd0mixYMEChg0b\nRqNGb0d0b1W1iIuL4/79+3z33XdMnz6d7777jpo1a/Lpp58SFxenSZM1hqpaWFhYsGXLFkJDQ+nQ\noQMdOnQgNDSUjRs3VrmtFaX526q0jgbKJ0BnRUVVLXLJyMhgypQp6OvrM2vWLHWbV6aoosXhw4e5\nf/8+EydO1KRpZY4qWsjlctLS0vj2228ZMGAAbm5u+Pv7U61aNbZt26ZJczWKKlo8ffqUL774Ajs7\nO9avX8/69euxt7fns88+IzIyUpPmVkhUvXZWWkcjAnTmoaoWuUiShLe3NxEREaxbtw4jIyNNmFkm\nqKJFZmYmS5YsYdy4ccjlcpKTkxVhkl68eKEUMqkyoer3Ivfzb9eunaLMwMAAOzs77t69q35DywBV\ntdi4cSPZ2dmsWrUKNzc33NzcWLVqFdWqVWPTpk2aNLnCUZprZ6V1NCJAZx6qapHLwoULOXbsGGvW\nrKFp06aaMrNMUEWLFy9eEB0dzaJFi3BycsLJyYmBAwcCMHXqVD744AON260JVP1eNG3aFC0trXy/\nVEtyh1zRUFWLe/fu0axZM3R0dBRlurq6NGvWjIcPH2rM3opIaa6dldbRiACdeaiqBcDatWvZtm0b\nS5cupW3btpo2VeOoooW+vj5btmxReq1YsQIALy8vli1bVia2qxtVvxddunRBkiR+//13RVlKSgo3\nbtygefPmGrVZU6iqhaWlJXfu3CEjI0NRlpGRwZ07dyrtHhpVKc21s9qcOXPmaNg+jWBtbc3u3bv5\n/fffMTc35+zZs6xYsYJRo0bRuXNnRb2ePXsSHh5O9+7dAahXrx5Xr14lMDCQevXqcf/+febMmUPT\npk2ZMmVKeZ1OqVBVi0OHDjF37lw++OAD2rVrR3R0tOKlq6tLzZo1y+uUVEYVLbS1talfv77SK9f5\njBo1ivbt25fjGamOqt8LCwsLbt68yc6dO6lduzYxMTHMnz+fxMRElixZQo0aNcrrlFRGVS3MzMz4\n4Ycf+PPPP6lVqxb379/Hx8eHW7duMW/ePExNTcvrlErFixcvOHbsGBEREZw5c4akpCTq1KlDREQE\nVlZW6OjoqPfaWbJtPhWLO3fuSCNGjJAcHBykjh07SitXrpSysrKU6nTt2lXy9vZWKktKSpJmzpwp\ntWnTRnrvvfckLy+vAjcvViZU0cLb21uSyWQFvvbu3VvWp6A2VP1evMqjR48q/YZNSVJdi9TUVGn2\n7NmSs7Oz5ODgII0aNUoKDw8vS9PVjqpanD17Vho2bJjk5OQkOTk5SZ988ol0/vz5sjRd7eR+vwt6\nPXr0SJIk9V47RVBNgUAgEGiUSvuMRiAQCASVA+FoBAKBQKBRhKMRCAQCgUYRjkYgEAgEGkU4GoFA\nIBBoFOFoBAKBQKBRhKMRqI19+/ZhY2NT4GvdunUl6isrKwsbGxv8/f01ZG3FYM+ePdjY2BAdHa0o\n2759OwcOHChW3crCoUOH2LJlS3mbISgnKm0qZ0HFZfHixTRu3FiprF69euVjTAWne/fuWFtbK4Wc\n37lzJ6ampvkSjxVUt7IQFBTEvXv3GDlyZHmbIigHhKMRqB0bGxtFpk5B0ZiYmBTbcZSkrqbJyMhA\nV1e3vM0QVBLE1JmgzPnf//7H4MGDcXJyom3btgwZMoSQkJA3touLi+Orr77Czc0Ne3t7XFxcGDFi\nBNeuXVOqt2/fPgYPHoyjoyNt2rRh0qRJxYq0u3LlSmxsbAgPD+fTTz+lVatWtGvXjjlz5vDixQul\nus+fP2fhwoV07twZe3t7unbtytKlS0lPT1eqFxwczIcffkjr1q1577336N27N4sXL1Ycf306zM3N\njTt37nDu3DnFtKOnp2eBdT/77DN69+6d7zwkSaJ79+5MmDBBUfby5UtWrlxJz549sbe3x9XVlQUL\nFpCWlvZGXTw8PBg8eDCnT59m8ODBODg4sGHDBiBnSszT05OOHTvSsmVL+vXrR0BAgFIQSg8PD379\n9VcePnyoOKeePXsqjicmJrJgwQK6dOmCvb093bp1Y9WqVWRlZb3RNkHlQNzRCNROdna20kVCS0uL\natWqKd7HxMQwYsQI6tatS1ZWFufOnWPq1Km8ePGiyJD806ZNIzo6Gi8vL6ysrEhMTOTq1atKOTJW\nrlzJ+vXr8fDwYMqUKaSkpLBmzRo8PDz46aefihUEceLEiQwcOBBPT0+uXr3Kd999R3R0NAEBAUBO\nYrDx48cTFhbGpEmTsLe358qVKwQEBHDr1i3FRfjChQt4eXkxfPhwvLy80NbW5tGjR9y8ebPQsQMC\nAvjiiy8wNjbmP//5D0Ch+VI++OADpkyZwqVLl2jTpo2i/MKFCzx+/JgZM2YAOc+7xo0bR3h4OJ99\n9hn29vZERESwatUq7ty5w/fff//G8P+RkZH897//5V//+hcNGjRQ2PTgwQO6d+/O6NGj0dPTIzw8\nnICAAB48eMCiRYsAmD9/Pt988w2RkZH4+voCoKenB+Tkg/Hw8CA1NZUJEybw7rvvcvXqVfz9/YmK\nilL0IajkqD9cm6Cqsnfv3gKD9LVq1arQNtnZ2VJmZqbk7e0tDR48WFGemZkpyWQyac2aNYoyBwcH\nadu2bYX29fDhQ8nW1lZavny5UnlUVJTk6OgoLVu2rEj7V6xYIclkMmnlypVK5f7+/pJMJpPCwsIk\nSZKkY8eOSTKZTNqxY4dSvY0bN0oymUw6e/asJEmStHbtWqldu3ZFjvnjjz9KMplMioqKUpS5u7tL\no0aNemPd9PR0ydnZWfr666+V6s2cOVNydnaW0tPTJUmSpP3790symUw6ffq0Ur2QkBBJJpNJp06d\nKtLGoUOHSjKZTLpy5UqR9eRyuZSZmSkFBgZKtra2UnJysuLYZ599JvXo0SNfm9WrV0stWrSQbt++\nrVSeq2VERESRYwoqB2LqTKB2li1bRmBgoOK1fft2pePnzp1j9OjRuLi40KJFC+zs7Ni/f3++xFSv\n4+joyNq1a9m8eTPh4eHI5XKl42fOnCE7O5v+/fuTlZWleJmamtK8eXMuXLhQLPvd3d0LfJ/bPjdP\nS//+/ZXq5T68P3/+vMLehIQEvLy8OH78OAkJCcUav7jo6urSt29fjhw5wsuXL4Gc8O8hISH0799f\n8Qzl5MmTmJqa0r59eyVdXF1d0dLSKpYuZmZmtGrVKl/533//zYwZM+jcuTN2dnbY2dnx1VdfkZ2d\nzYMHD97Y76lTp7Czs6NJkyZKtuXmN3k194mg8iKmzgRqp1mzZoUuBrh48SJjxoyhQ4cOzJkzB3Nz\nc6pXr862bds4dOhQkf2uWrWKNWvW8MMPP+Dj44OxsTH9+vVj6tSpGBgYEB8fD0C/fv0KbP/6SrjC\neH16rU6dOkDOswSApKQk9PX1MTAwUKpnYmJC9erVFfXat2/P6tWr2bp1K1988QVZWVk4OjoyefJk\nOnXqVCxb3sQHH3zAjh07CA0NZcCAAfz888+kpaUxePBgRZ24uDji4uKws7MrsI/iOEBzc/N8ZSkp\nKQwbNoxatWrxxRdf0KhRI/T09Lhy5QrffvutwvkVRVxcHE+ePCmVbYKKj3A0gjLlyJEj1KhRg+++\n+05p1VJmZuYb25qYmPDNN98o5vtDQkJYsWIFaWlpLFq0iNq1awM5zzkKehaT+1zgTcTFxSn6AhQO\nzNjYWPFvWloaqampSs7m2bNnZGVlKeoB9OrVi169epGRkcGlS5fw8/PjX//6F4cPH6ZRo0bFsqco\nHB0dsba2Zv/+/QwYMID9+/djY2NDixYtFHVq166Nubl5oXuSVF3JdvbsWeLj4/Hz86N169aK8hs3\nbhS7j9q1a2NsbMzcuXMLPG5hYaGSbYKKhXA0gjIld2GAtnberG1sbCwnTpwoUT+WlpaMGTOGX375\nhVu3bgHg6uqKtrY2jx8/pmvXrirbePjwYaWMgYcPHwbAyckJyLlT2bx5M4cOHcLDw0NR7+DBg4rj\nr6Orq4uLiwsAnp6e3L17t1BHo6urW6y7gVwGDRrE8uXLuXTpEr///jszZ85UOu7m5sbRo0fR0dFR\nayrm3AUEOjo6ijJJkggMDMxXt7BzcnNzY8uWLZibmwun8hYjHI2gTOncuTNbt27lyy+/ZMiQITx9\n+hR/f3/MzMx4/Phxoe0SEhIYO3Ys/fr1o2nTptSoUYMLFy4QFhbGp59+CkCjRo0YP348ixcv5sGD\nB7i4uGBgYEBsbCyXLl3C2tqaYcOGvdHGQ4cOoa2tTZs2bRSrzrp164ajoyOQc3Fs164dCxcuJDk5\nGXt7e0W9Ll26KBzKypUriYuLo3379lhYWJCQkMCGDRswMjKiZcuWhY5vbW1NSEgIP//8M5aWlhgY\nGNCkSZNC6w8cOJAVK1bg5eVF9erVGTBggNLxQYMG8dNPPzFmzBg8PT0VdztRUVGcOXOGMWPGFGlP\nYbRp0wYDAwNmz57NpEmTkCSJnTt3Kq0CfPWcQkNDFUu0a9SogUwmY+zYsYSGhjJs2DA8PT1p1qwZ\nGRkZPHnyhJMnTzJ37lzq1q1bYtsEFQvhaARlSqdOnZg7dy6bNm3il19+oX79+owdO5bIyEjWr19f\naLuaNWtib2/P/v37efLkCZIkYWVlxZQpUxg7dqyi3pQpU5DJZGzdupW9e/cil8sxMzPjvffew8HB\noVg2rlmzhmXLlrFp0yb09PT46KOPFEuFAbS1tQkICMDX15cdO3YQFxeHubk5np6eTJ48WVGvZcuW\nbN++nSVLlpCQkICxsTGtWrVi/vz5iuc+BTF58mRiYmKYOXMmaWlpuLi48P333xda38zMjE6dOvHr\nr7/SvXv3fFNh1atXZ+PGjWzatImDBw+yevVqdHV1sbS0xMXFBSsrq2Lp8jp16tQhICCAxYsX4+Xl\nRa1atejfvz/Dhw9X2sMDMHLkSG7dusXixYtJSUmhYcOGHD16FAMDA3bv3o2/vz9bt24lMjISfX19\n6tevT6dOnTA0NFTJNkHFQqRyFgj+YeXKlQQEBHD58mXeeeed8jZHIHhrEMubBQKBQKBRhKMRCAQC\ngUYRU2cCgUAg0CjijkYgEAgEGkU4GoFAIBBoFOFoBAKBQKBRhKMRCAQCgUYRjkYgEAgEGuX/AQsO\nM1bzvR5VAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f024b8f4910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZoAAAEkCAYAAAAWxvdmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nH7TI34Cnal0QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f024b7c6bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZoAAAEkCAYAAAAWxvdmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f02208aadd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "plot_roc(y,GNB)\n",
    "plot_roc(y,XGB) \n",
    "plot_roc(y,Lr) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Confusion Matrix Stats : Gaussian NB \n",
      "NOT_SURVIVE/NOT_SURVIVE: 83.68% (359/429)\n",
      "NOT_SURVIVE/SURVIVE: 16.32% (70/429)\n",
      "SURVIVE/NOT_SURVIVE: 29.52% (80/271)\n",
      "SURVIVE/SURVIVE: 70.48% (191/271)\n",
      "\n",
      "Confusion Matrix Stats : XGBoost\n",
      "NOT_SURVIVE/NOT_SURVIVE: 89.04% (382/429)\n",
      "NOT_SURVIVE/SURVIVE: 10.96% (47/429)\n",
      "SURVIVE/NOT_SURVIVE: 33.58% (91/271)\n",
      "SURVIVE/SURVIVE: 66.42% (180/271)\n",
      "\n",
      "Confusion Matrix Stats : Lrmodel\n",
      "NOT_SURVIVE/NOT_SURVIVE: 99.53% (427/429)\n",
      "NOT_SURVIVE/SURVIVE: 0.47% (2/429)\n",
      "SURVIVE/NOT_SURVIVE: 94.46% (256/271)\n",
      "SURVIVE/SURVIVE: 5.54% (15/271)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAKECAYAAACJsOyvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAOBy/x/fdmzeZM6hBQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f02203d0510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAKECAYAAACJsOyvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f02203d0790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAKECAYAAACJsOyvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0220554c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = ['NOT_SURVIVE', 'SURVIVE']    \n",
    "plot_cm(y, GNB, labels)\n",
    "plot_cm(y, XGB, labels)\n",
    "plot_cm(y,Lr,labels) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
